Alternatives to Azure Data Lake
Compare Azure Data Lake alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Azure Data Lake in 2026. Compare features, ratings, user reviews, pricing, and more from Azure Data Lake competitors and alternatives in order to make an informed decision for your business.
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Teradata VantageCloud
Teradata
Teradata VantageCloud: The complete cloud analytics and data platform for AI. Teradata VantageCloud is an enterprise-grade, cloud-native data and analytics platform that unifies data management, advanced analytics, and AI/ML capabilities in a single environment. Designed for scalability and flexibility, VantageCloud supports multi-cloud and hybrid deployments, enabling organizations to manage structured and semi-structured data across AWS, Azure, Google Cloud, and on-premises systems. It offers full ANSI SQL support, integrates with open-source tools like Python and R, and provides built-in governance for secure, trusted AI. VantageCloud empowers users to run complex queries, build data pipelines, and operationalize machine learning models—all while maintaining interoperability with modern data ecosystems. -
2
Files.com
Files.com
Files.com is a cloud-native Managed File Transfer (MFT) platform that unifies file transfers, sharing, and automation across any cloud, protocol, or partner. It connects 50+ storage systems — including Amazon S3, Azure, Google Drive, SharePoint, Dropbox, and Box — presenting them as a single seamless namespace. Files.com supports SFTP, FTP/FTPS, AS2, HTTPS, WebDAV, and REST APIs, making it compatible with virtually any system or partner. Automated workflows eliminate manual scripts and reduce admin overhead by up to 90%. Enterprise-grade security includes AES-256 encryption, SOC 2 Type II certification, HIPAA/GDPR compliance, full audit trails, SSO (Okta, Azure AD, and more), and 2FA. With a 99.99% uptime history and zero data breaches in 15 years, Files.com is trusted by IT teams in finance, healthcare, and technology. Available via web, desktop (Windows/macOS), mobile (iOS/Android), and on-premises agent (Windows/macOS/Linux) -
3
AnalyticsCreator
AnalyticsCreator
AnalyticsCreator is a metadata-driven data warehouse automation application for teams working in the Microsoft data ecosystem. It enables data engineers to design, generate, and maintain production-ready data products across Microsoft SQL Server, Azure Data Factory, and Microsoft Fabric. By using centralized metadata, AnalyticsCreator generates ELT pipelines, dimensional models, historization logic, and analytical models in a consistent, version-controlled way. This reduces manual implementation effort and tool sprawl while ensuring transparency through built-in lineage tracking and clear visibility into data dependencies and change impact. With CI/CD integration via Azure DevOps and GitHub, plus support for custom SQL, AnalyticsCreator helps data teams scale delivery, enforce standards, and maintain control as complexity grows. -
4
Amazon S3
Amazon
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. This means customers of all sizes and industries can use it to store and protect any amount of data for a range of use cases, such as data lakes, websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Amazon S3 provides easy-to-use management features so you can organize your data and configure finely-tuned access controls to meet your specific business, organizational, and compliance requirements. Amazon S3 is designed for 99.999999999% (11 9's) of durability, and stores data for millions of applications for companies all around the world. Scale your storage resources up and down to meet fluctuating demands, without upfront investments or resource procurement cycles. Amazon S3 is designed for 99.999999999% (11 9’s) of data durability. -
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OneBlox
StorageCraft
OneBlox employs a seamless scale-out Ring architecture supporting multiple OneBlox appliances presenting a single global file system. A Ring may consist of one or multiple OneBlox, scaling from a few TBs to hundreds of TBs of raw flash or multiple PBs of hard-drive storage capacity. As business storage requirements change, OneBlox is extremely agile; simply add any number of drives, at any time, and in any capacity granularity to meet your storage requirements. OneBlox simply grows the global storage pool with zero configuration and no application downtime. OneBlox uniquely supports VMware and Hyper-V environments by enabling virtual machines to utilize scale-out NFS datastores. Consolidate multiple NFS datastores in a single OneBlox Ring and scale to hundreds of TBs with OneBlox’s advanced data reduction. Need high performance? OneBlox 5210 is an all-flash array for consolidating performance hungry virtual machines. -
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OpenIO
OpenIO
OpenIO is a software-defined open source object storage solution ideal for Big Data, HPC and AI. With its distributed grid architecture and unique self-learning ConsciousGrid™ technology, OpenIO scales easily without mandatory data rebalancing, while delivering consistent high performance. OpenIO is S3 compatible and can be deployed on-premises or cloud-hosted, on any hardware that you choose. Scale seamlessly from Terabytes to Exabytes. Simply add nodes to expand capacity, without rebalancing data, and watch as performance increases linearly. Transfer data at 1 Tbps and beyond. Experience consistent high performance, even during scaling operations. Ideal for capacity-intensive and challenging workloads. Use servers and storage media that suit your evolving needs. Avoid vendor lock-in. You can combine heterogenous hardware at any time, of different specs, generations, and capacities. -
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Aura Object Store
Akamai
Aura Object Store. Highly scalable, persistent media content store for CDN content origination. Aura Object Store is a replicated HTTP object store that stores media content persistently for CDN content origination. It supports file ingest via multiple protocols and originates that content for both linear and VoD applications. Designed specifically for operators seeking a resilient online media storage solution to supplement their CDNs, Aura Object Store is easy to manage, affordable and scales to grow with business needs. Aura Object Store provides the root of the CDN hierarchy, serving cache misses from multiple CDN caching tiers downstream. Based on standard HTTP or HTTPS delivery, it offers a scale-out content delivery architecture for redundancy and storage expansion in which several nodes are connected to form a common storage cluster with a single virtualized namespace. -
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Azure Data Factory
Microsoft
Integrate data silos with Azure Data Factory, a service built for all data integration needs and skill levels. Easily construct ETL and ELT processes code-free within the intuitive visual environment, or write your own code. Visually integrate data sources using more than 90+ natively built and maintenance-free connectors at no added cost. Focus on your data—the serverless integration service does the rest. Data Factory provides a data integration and transformation layer that works across your digital transformation initiatives. Data Factory can help independent software vendors (ISVs) enrich their SaaS apps with integrated hybrid data as to deliver data-driven user experiences. Pre-built connectors and integration at scale enable you to focus on your users while Data Factory takes care of the rest. -
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Data Lakes on AWS
Amazon
Many Amazon Web Services (AWS) customers require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. A data lake is a new and increasingly popular way to store and analyze data because it allows companies to manage multiple data types from a wide variety of sources, and store this data, structured and unstructured, in a centralized repository. The AWS Cloud provides many of the building blocks required to help customers implement a secure, flexible, and cost-effective data lake. These include AWS managed services that help ingest, store, find, process, and analyze both structured and unstructured data. To support our customers as they build data lakes, AWS offers the data lake solution, which is an automated reference implementation that deploys a highly available, cost-effective data lake architecture on the AWS Cloud along with a user-friendly console for searching and requesting datasets. -
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Azure Blob Storage
Microsoft
Massively scalable and secure object storage for cloud-native workloads, archives, data lakes, high-performance computing, and machine learning. Azure Blob Storage helps you create data lakes for your analytics needs, and provides storage to build powerful cloud-native and mobile apps. Optimize costs with tiered storage for your long-term data, and flexibly scale up for high-performance computing and machine learning workloads. Blob storage is built from the ground up to support the scale, security, and availability needs of mobile, web, and cloud-native application developers. Use it as a cornerstone for serverless architectures such as Azure Functions. Blob storage supports the most popular development frameworks, including Java, .NET, Python, and Node.js, and is the only cloud storage service that offers a premium, SSD-based object storage tier for low-latency and interactive scenarios.Starting Price: $0.00099 -
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The Qlik Data Integration platform for managed data lakes automates the process of providing continuously updated, accurate, and trusted data sets for business analytics. Data engineers have the agility to quickly add new sources and ensure success at every step of the data lake pipeline from real-time data ingestion, to refinement, provisioning, and governance. A simple and universal solution for continually ingesting enterprise data into popular data lakes in real-time. A model-driven approach for quickly designing, building, and managing data lakes on-premises or in the cloud. Deliver a smart enterprise-scale data catalog to securely share all of your derived data sets with business users.
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ELCA Smart Data Lake Builder
ELCA Group
Classical Data Lakes are often reduced to basic but cheap raw data storage, neglecting significant aspects like transformation, data quality and security. These topics are left to data scientists, who end up spending up to 80% of their time acquiring, understanding and cleaning data before they can start using their core competencies. In addition, classical Data Lakes are often implemented by separate departments using different standards and tools, which makes it harder to implement comprehensive analytical use cases. Smart Data Lakes solve these various issues by providing architectural and methodical guidelines, together with an efficient tool to build a strong high-quality data foundation. Smart Data Lakes are at the core of any modern analytics platform. Their structure easily integrates prevalent Data Science tools and open source technologies, as well as AI and ML. Their storage is cheap and scalable, supporting both unstructured data and complex data structures.Starting Price: Free -
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AWS Lake Formation
Amazon
AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis. A data lake lets you break down data silos and combine different types of analytics to gain insights and guide better business decisions. Setting up and managing data lakes today involves a lot of manual, complicated, and time-consuming tasks. This work includes loading data from diverse sources, monitoring those data flows, setting up partitions, turning on encryption and managing keys, defining transformation jobs and monitoring their operation, reorganizing data into a columnar format, deduplicating redundant data, and matching linked records. Once data has been loaded into the data lake, you need to grant fine-grained access to datasets, and audit access over time across a wide range of analytics and machine learning (ML) tools and services. -
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lakeFS
Treeverse
lakeFS enables you to manage your data lake the way you manage your code. Run parallel pipelines for experimentation and CI/CD for your data. Simplifying the lives of engineers, data scientists and analysts who are transforming the world with data. lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes. With lakeFS you can build repeatable, atomic and versioned data lake operations, from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage and Google Cloud Storage (GCS) as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, Presto, etc. lakeFS provides a Git-like branching and committing model that scales to exabytes of data by utilizing S3, GCS, or Azure Blob for storage. -
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Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
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Qlik Compose
Qlik
Qlik Compose for Data Warehouses provides a modern approach by automating and optimizing data warehouse creation and operation. Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, all whilst leveraging best practices and proven design patterns. Qlik Compose for Data Warehouses dramatically reduces the time, cost and risk of BI projects, whether on-premises or in the cloud. Qlik Compose for Data Lakes automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments. -
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Cribl Lake
Cribl
Storage that doesn’t lock data in. Get up and running fast with a managed data lake. Easily store, access, and retrieve data, without being a data expert. Cribl Lake keeps you from drowning in data. Easily store, manage, enforce policy on, and access data when you need. Dive into the future with open formats and unified retention, security, and access control policies. Let Cribl handle the heavy lifting so data can be usable and valuable to the teams and tools that need it. Minutes, not months to get up and running with Cribl Lake. Zero configuration with automated provisioning and out-of-the-box integrations. Streamline workflows with Stream and Edge for powerful data ingestion and routing. Cribl Search unifies queries no matter where data is stored, so you can get value from data without delays. Take an easy path to collect and store data for long-term retention. Comply with legal and business requirements for data retention by defining specific retention periods. -
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Alibaba Cloud Data Lake Formation
Alibaba Cloud
A data lake is a centralized repository used for big data and AI computing. It allows you to store structured and unstructured data at any scale. Data Lake Formation (DLF) is a key component of the cloud-native data lake framework. DLF provides an easy way to build a cloud-native data lake. It seamlessly integrates with a variety of compute engines and allows you to manage the metadata in data lakes in a centralized manner and control enterprise-class permissions. Systematically collects structured, semi-structured, and unstructured data and supports massive data storage. Uses an architecture that separates computing from storage. You can plan resources on demand at low costs. This improves data processing efficiency to meet the rapidly changing business requirements. DLF can automatically discover and collect metadata from multiple engines and manage the metadata in a centralized manner to solve the data silo issues. -
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Lentiq
Lentiq
Lentiq is a collaborative data lake as a service environment that’s built to enable small teams to do big things. Quickly run data science, machine learning and data analysis at scale in the cloud of your choice. With Lentiq, your teams can ingest data in real time and then process, clean and share it. From there, Lentiq makes it possible to build, train and share models internally. Simply put, data teams can collaborate with Lentiq and innovate with no restrictions. Data lakes are storage and processing environments, which provide ML, ETL, schema-on-read querying capabilities and so much more. Are you working on some data science magic? You definitely need a data lake. In the Post-Hadoop era, the big, centralized data lake is a thing of the past. With Lentiq, we use data pools, which are multi-cloud, interconnected mini-data lakes. They work together to give you a stable, secure and fast data science environment. -
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Upsolver
Upsolver
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read. Easy visual IDE to accelerate building pipelines. Add Upserts and Deletes to data lake tables. Blend streaming and large-scale batch data. Automated schema evolution and reprocessing from previous state. Automatic orchestration of pipelines (no DAGs). Fully-managed execution at scale. Strong consistency guarantee over object storage. Near-zero maintenance overhead for analytics-ready data. Built-in hygiene for data lake tables including columnar formats, partitioning, compaction and vacuuming. 100,000 events per second (billions daily) at low cost. Continuous lock-free compaction to avoid “small files” problem. Parquet-based tables for fast queries. -
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Kylo
Teradata
Kylo is an open source enterprise-ready data lake management software platform for self-service data ingest and data preparation with integrated metadata management, governance, security and best practices inspired by Think Big's 150+ big data implementation projects. Self-service data ingest with data cleansing, validation, and automatic profiling. Wrangle data with visual sql and an interactive transform through a simple user interface. Search and explore data and metadata, view lineage, and profile statistics. Monitor health of feeds and services in the data lake. Track SLAs and troubleshoot performance. Design batch or streaming pipeline templates in Apache NiFi and register with Kylo to enable user self-service. Organizations can expend significant engineering effort moving data into Hadoop yet struggle to maintain governance and data quality. Kylo dramatically simplifies data ingest by shifting ingest to data owners through a simple guided UI. -
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Dremio
Dremio
Dremio delivers lightning-fast queries and a self-service semantic layer directly on your data lake storage. No moving data to proprietary data warehouses, no cubes, no aggregation tables or extracts. Just flexibility and control for data architects, and self-service for data consumers. Dremio technologies like Data Reflections, Columnar Cloud Cache (C3) and Predictive Pipelining work alongside Apache Arrow to make queries on your data lake storage very, very fast. An abstraction layer enables IT to apply security and business meaning, while enabling analysts and data scientists to explore data and derive new virtual datasets. Dremio’s semantic layer is an integrated, searchable catalog that indexes all of your metadata, so business users can easily make sense of your data. Virtual datasets and spaces make up the semantic layer, and are all indexed and searchable. -
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Amazon Security Lake
Amazon
Amazon Security Lake automatically centralizes security data from AWS environments, SaaS providers, on-premises, and cloud sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization. You can also improve the protection of your workloads, applications, and data. Security Lake has adopted the Open Cybersecurity Schema Framework (OCSF), an open standard. With OCSF support, the service normalizes and combines security data from AWS and a broad range of enterprise security data sources. Use your preferred analytics tools to analyze your security data while retaining complete control and ownership over that data. Centralize data visibility from cloud and on-premises sources across your accounts and AWS Regions. Streamline your data management at scale by normalizing your security data to an open standard.Starting Price: $0.75 per GB per month -
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Infor Data Lake
Infor
Solving today’s enterprise and industry challenges requires big data. The ability to capture data from across your enterprise—whether generated by disparate applications, people, or IoT infrastructure–offers tremendous potential. Infor’s Data Lake tools deliver schema-on-read intelligence along with a fast, flexible data consumption framework to enable new ways of making key decisions. With leveraged access to your entire Infor ecosystem, you can start capturing and delivering big data to power your next generation analytics and machine learning strategies. Infinitely scalable, the Infor Data Lake provides a unified repository for capturing all of your enterprise data. Grow with your insights and investments, ingest more content for better informed decisions, improve your analytics profiles, and provide rich data sets to build more powerful machine learning processes. -
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DataLakeHouse.io
DataLakeHouse.io
DataLakeHouse.io (DLH.io) Data Sync provides replication and synchronization of operational systems (on-premise and cloud-based SaaS) data into destinations of their choosing, primarily Cloud Data Warehouses. Built for marketing teams and really any data team at any size organization, DLH.io enables business cases for building single source of truth data repositories, such as dimensional data warehouses, data vault 2.0, and other machine learning workloads. Use cases are technical and functional including: ELT, ETL, Data Warehouse, Pipeline, Analytics, AI & Machine Learning, Data, Marketing, Sales, Retail, FinTech, Restaurant, Manufacturing, Public Sector, and more. DataLakeHouse.io is on a mission to orchestrate data for every organization particularly those desiring to become data-driven, or those that are continuing their data driven strategy journey. DataLakeHouse.io (aka DLH.io) enables hundreds of companies to managed their cloud data warehousing and analytics solutions.Starting Price: $99 -
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Electrik.Ai
Electrik.Ai
Automatically ingest marketing data into any data warehouse or cloud file storage of your choice such as BigQuery, Snowflake, Redshift, Azure SQL, AWS S3, Azure Data Lake, Google Cloud Storage with our fully managed ETL pipelines in the cloud. Our hosted marketing data warehouse integrates all your marketing data and provides ad insights, cross-channel attribution, content insights, competitor Insights, and more. Our customer data platform performs identity resolution in real-time across data sources thus enabling a unified view of the customer and their journey. Electrik.AI is a cloud-based marketing analytics software and full-service platform. Electrik.AI’s Google Analytics Hit Data Extractor enriches and extracts the un-sampled hit level data sent to Google Analytics from the website or application and periodically ships it to your desired destination database/data warehouse or file/data lake.Starting Price: $49 per month -
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Delta Lake
Delta Lake
Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. Data lakes typically have multiple data pipelines reading and writing data concurrently, and data engineers have to go through a tedious process to ensure data integrity, due to the lack of transactions. Delta Lake brings ACID transactions to your data lakes. It provides serializability, the strongest level of isolation level. Learn more at Diving into Delta Lake: Unpacking the Transaction Log. In big data, even the metadata itself can be "big data". Delta Lake treats metadata just like data, leveraging Spark's distributed processing power to handle all its metadata. As a result, Delta Lake can handle petabyte-scale tables with billions of partitions and files at ease. Delta Lake provides snapshots of data enabling developers to access and revert to earlier versions of data for audits, rollbacks or to reproduce experiments. -
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Simplify big data operations and build intelligent knowledge libraries with Data Lake Governance Center (DGC), a one-stop data lake operations platform that manages data design, development, integration, quality, and assets. Build an enterprise-class data lake governance platform with an easy-to-use visual interface. Streamline data lifecycle processes, utilize metrics and analytics, and ensure good governance across your enterprise. Define and monitor data standards, and get real-time alerts. Build data lakes quicker by easily setting up data integrations, models, and cleaning rules, to enable the discovery of new reliable data sources. Maximize the business value of data. With DGC, end-to-end data operations solutions can be designed for scenarios such as smart government, smart taxation, and smart campus. Gain new insights into sensitive data across your entire organization. DGC allows enterprises to define business catalogs, classifications, and terms.Starting Price: $428 one-time payment
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Azure Data Lake Storage
Microsoft
Eliminate data silos with a single storage platform. Optimize costs with tiered storage and policy management. Authenticate data using Azure Active Directory (Azure AD) and role-based access control (RBAC). And help protect data with security features like encryption at rest and advanced threat protection. Highly secure with flexible mechanisms for protection across data access, encryption, and network-level control. Single storage platform for ingestion, processing, and visualization that supports the most common analytics frameworks. Cost optimization via independent scaling of storage and compute, lifecycle policy management, and object-level tiering. Meet any capacity requirements and manage data with ease, with the Azure global infrastructure. Run large-scale analytics queries at consistently high performance. -
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NewEvol
Sattrix Software Solutions
NewEvol is the technologically advanced product suite that uses data science for advanced analytics to identify abnormalities in the data itself. Supported by visualization, rule-based alerting, automation, and responses, NewEvol becomes a more compiling proposition for any small to large enterprise. Machine Learning (ML) and security intelligence feed makes NewEvol a more robust system to cater to challenging business demands. NewEvol Data Lake is super easy to deploy and manage. You don’t require a team of expert data administrators. As your company’s data need grows, it automatically scales and reallocates resources accordingly. NewEvol Data Lake has extensive data ingestion to perform enrichment across multiple sources. It helps you ingest data from multiple formats such as delimited, JSON, XML, PCAP, Syslog, etc. It offers enrichment with the help of a best-of-breed contextually aware event analytics model. -
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Qubole
Qubole
Qubole is a simple, open, and secure Data Lake Platform for machine learning, streaming, and ad-hoc analytics. Our platform provides end-to-end services that reduce the time and effort required to run Data pipelines, Streaming Analytics, and Machine Learning workloads on any cloud. No other platform offers the openness and data workload flexibility of Qubole while lowering cloud data lake costs by over 50 percent. Qubole delivers faster access to petabytes of secure, reliable and trusted datasets of structured and unstructured data for Analytics and Machine Learning. Users conduct ETL, analytics, and AI/ML workloads efficiently in end-to-end fashion across best-of-breed open source engines, multiple formats, libraries, and languages adapted to data volume, variety, SLAs and organizational policies. -
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Dimodelo
Dimodelo
Stay focused on delivering valuable and impressive reporting, analytics and insights, instead of being stuck in data warehouse code. Don’t let your data warehouse become a jumble of 100’s of hard-to-maintain pipelines, notebooks, stored procedures, tables. and views etc. Dimodelo DW Studio dramatically reduces the effort required to design, build, deploy and run a data warehouse. Design, generate and deploy a data warehouse targeting Azure Synapse Analytics. Generating a best practice architecture utilizing Azure Data Lake, Polybase and Azure Synapse Analytics, Dimodelo Data Warehouse Studio delivers a high-performance, modern data warehouse in the cloud. Utilizing parallel bulk loads and in-memory tables, Dimodelo Data Warehouse Studio generates a best practice architecture that delivers a high-performance, modern data warehouse in the cloud.Starting Price: $899 per month -
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Openbridge
Openbridge
Uncover insights to supercharge sales growth using code-free, fully-automated data pipelines to data lakes or cloud warehouses. A flexible, standards-based platform to unify sales and marketing data for automating insights and smarter growth. Say goodbye to messy, expensive manual data downloads. Always know what you’ll pay and only pay for what you use. Fuel your tools with quick access to analytics-ready data. As certified developers, we only work with secure, official APIs. Get started quickly with data pipelines from popular sources. Pre-built, pre-transformed, and ready-to-go data pipelines. Unlock data from Amazon Vendor Central, Amazon Seller Central, Instagram Stories, Facebook, Amazon Advertising, Google Ads, and many others. Code-free data ingestion and transformation processes allow teams to realize value from their data quickly and cost-effectively. Data is always securely stored directly in a trusted, customer-owned data destination like Databricks, Amazon Redshift, etc.Starting Price: $149 per month -
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Azure Data Lake Analytics
Microsoft
Easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and .NET over petabytes of data. With no infrastructure to manage, you can process data on demand, scale instantly, and only pay per job. Process big data jobs in seconds with Azure Data Lake Analytics. There is no infrastructure to worry about because there are no servers, virtual machines, or clusters to wait for, manage, or tune. Instantly scale the processing power, measured in Azure Data Lake Analytics Units (AU), from one to thousands for each job. You only pay for the processing that you use per job. Act on all of your data with optimized data virtualization of your relational sources such as Azure SQL Database and Azure Synapse Analytics. Your queries are automatically optimized by moving processing close to the source data without data movement, which maximizes performance and minimizes latency.Starting Price: $2 per hour -
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Archon Data Store
Platform 3 Solutions
Archon Data Store is a next-generation enterprise data archiving platform designed to help organizations manage rapid data growth, reduce legacy application costs, and meet global compliance standards. Built on a modern Lakehouse architecture, Archon Data Store unifies data lakes and data warehouses to deliver secure, scalable, and analytics-ready archival storage. The platform supports on-premise, cloud, and hybrid deployments with AES-256 encryption, audit trails, metadata governance, and role-based access control. Archon Data Store offers intelligent storage tiering, high-performance querying, and seamless integration with BI tools. It enables efficient application decommissioning, cloud migration, and digital modernization while transforming archived data into a strategic asset. With Archon Data Store, organizations can ensure long-term compliance, optimize storage costs, and unlock AI-driven insights from historical data. -
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BryteFlow
BryteFlow
BryteFlow builds the most efficient automated environments for analytics ever. It converts Amazon S3 into an awesome analytics platform by leveraging the AWS ecosystem intelligently to deliver data at lightning speeds. It complements AWS Lake Formation and automates the Modern Data Architecture providing performance and productivity. You can completely automate data ingestion with BryteFlow Ingest’s simple point-and-click interface while BryteFlow XL Ingest is great for the initial full ingest for very large datasets. No coding is needed! With BryteFlow Blend you can merge data from varied sources like Oracle, SQL Server, Salesforce and SAP etc. and transform it to make it ready for Analytics and Machine Learning. BryteFlow TruData reconciles the data at the destination with the source continually or at a frequency you select. If data is missing or incomplete you get an alert so you can fix the issue easily. -
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Hydrolix
Hydrolix
Hydrolix is a streaming data lake that combines decoupled storage, indexed search, and stream processing to deliver real-time query performance at terabyte-scale for a radically lower cost. CFOs love the 4x reduction in data retention costs. Product teams love 4x more data to work with. Spin up resources when you need them and scale to zero when you don’t. Fine-tune resource consumption and performance by workload to control costs. Imagine what you can build when you don’t have to sacrifice data because of budget. Ingest, enrich, and transform log data from multiple sources including Kafka, Kinesis, and HTTP. Return just the data you need, no matter how big your data is. Reduce latency and costs, eliminate timeouts, and brute force queries. Storage is decoupled from ingest and query, allowing each to independently scale to meet performance and budget targets. Hydrolix’s high-density compression (HDX) typically reduces 1TB of stored data to 55GB.Starting Price: $2,237 per month -
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Google Cloud Lakehouse
Google
Google Cloud Lakehouse is a storage engine designed to unify data warehouses and data lakes into a single, cohesive platform. It allows organizations to access and manage data in open formats such as Apache Iceberg, Parquet, and ORC. The platform enables users to work with a single copy of data without needing to duplicate or move it across systems. It provides fine-grained security controls to ensure proper data governance and access management. Google Cloud Lakehouse simplifies data operations by integrating analytics and storage capabilities. It supports modern data workflows, including big data processing and analytics. The platform is built to scale with enterprise data needs while maintaining performance and flexibility. Overall, it helps organizations streamline data management and unlock insights more efficiently.Starting Price: $5 per TB -
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Varada
Varada
Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance. -
40
Lyftrondata
Lyftrondata
Whether you want to build a governed delta lake, data warehouse, or simply want to migrate from your traditional database to a modern cloud data warehouse, do it all with Lyftrondata. Simply create and manage all of your data workloads on one platform by automatically building your pipeline and warehouse. Analyze it instantly with ANSI SQL, BI/ML tools, and share it without worrying about writing any custom code. Boost the productivity of your data professionals and shorten your time to value. Define, categorize, and find all data sets in one place. Share these data sets with other experts with zero codings and drive data-driven insights. This data sharing ability is perfect for companies that want to store their data once, share it with other experts, and use it multiple times, now and in the future. Define dataset, apply SQL transformations or simply migrate your SQL data processing logic to any cloud data warehouse. -
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IBM watsonx.data
IBM
Put your data to work, wherever it resides, with the open, hybrid data lakehouse for AI and analytics. Connect your data from anywhere, in any format, and access through a single point of entry with a shared metadata layer. Optimize workloads for price and performance by pairing the right workloads with the right query engine. Embed natural-language semantic search without the need for SQL, so you can unlock generative AI insights faster. Manage and prepare trusted data to improve the relevance and precision of your AI applications. Use all your data, everywhere. With the speed of a data warehouse, the flexibility of a data lake, and special features to support AI, watsonx.data can help you scale AI and analytics across your business. Choose the right engines for your workloads. Flexibly manage cost, performance, and capability with access to multiple open engines including Presto, Presto C++, Spark Milvus, and more. -
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Cloudflare R2
Cloudflare
Cloudflare R2 is a global object storage service that allows developers to store large amounts of unstructured data without the costly egress bandwidth fees associated with typical cloud storage services. It supports multiple scenarios, including storage for cloud-native applications, web content, podcast episodes, data lakes, and outputs for large batch processes such as machine learning model artifacts or datasets. R2 offers features like location hints to optimize data access, CORS configuration for interacting with objects, public buckets to expose contents directly to the Internet, and bucket-scoped tokens for granular access control. It integrates with Cloudflare Workers, enabling developers to perform authentication, route requests, and deploy edge functions across a network of over 330 data centers. Additionally, R2 supports Apache Iceberg through its data catalog, transforming object storage into a fully functional data warehouse without management overhead.Starting Price: $0.015 per GB -
43
Datametica
Datametica
At Datametica, our birds with unprecedented capabilities help eliminate business risks, cost, time, frustration, and anxiety from the entire process of data warehouse migration to the cloud. Migration of existing data warehouse, data lake, ETL, and Enterprise business intelligence to the cloud environment of your choice using Datametica automated product suite. Architecting an end-to-end migration strategy, with workload discovery, assessment, planning, and cloud optimization. Starting from discovery and assessment of your existing data warehouse to planning the migration strategy – Eagle gives clarity on what’s needed to be migrated and in what sequence, how the process can be streamlined, and what are the timelines and costs. The holistic view of the workloads and planning reduces the migration risk without impacting the business. -
44
Cribl Search
Cribl
Cribl Search delivers next-generation search-in-place technology, empowering users to explore, discover, and analyze data that was previously impossible – directly at its source, across any cloud, even data locked behind APIs. Effortlessly search your Cribl Lake or sift through data in major object stores like AWS S3, Amazon Security Lake, Azure Blob, and Google Cloud Storage, and enrich your insights by querying dozens of live API endpoints from various SaaS providers. The power of Cribl Search lies in its strategic approach: forward only the critical data to your systems of analysis, thus avoiding the cost of expensive storage. With native support for platforms such as Amazon Security Lake, AWS S3, Azure Blob, and Google Cloud Storage, Cribl Search delivers a first-of-its-kind ability to seamlessly analyze all data right at its source. Cribl Search allows users to search and analyze data wherever it is located, from debug logs at the edge to archived data in cold storage. -
45
Cazena
Cazena
Cazena’s Instant Data Lake accelerates time to analytics and AI/ML from months to minutes. Powered by its patented automated data platform, Cazena delivers the first SaaS experience for data lakes. Zero operations required. Enterprises need a data lake that easily supports all of their data and tools for analytics, machine learning and AI. To be effective, a data lake must offer secure data ingestion, flexible data storage, access and identity management, tool integration, optimization and more. Cloud data lakes are complicated to do yourself, which is why they require expensive teams. Cazena’s Instant Cloud Data Lakes are instantly production-ready for data loading and analytics. Everything is automated, supported on Cazena’s SaaS Platform with continuous Ops and self-service access via the Cazena SaaS Console. Cazena's Instant Data Lakes are turnkey and production-ready for secure data ingest, storage and analytics. -
46
Utilihive
Greenbird Integration Technology
Utilihive is a cloud-native big data integration platform, purpose-built for the digital data-driven utility, offered as a managed service (SaaS). Utilihive is the leading Enterprise-iPaaS (iPaaS) that is purpose-built for energy and utility usage scenarios. Utilihive provides both the technical infrastructure platform (connectivity, integration, data ingestion, data lake, API management) and pre-configured integration content or accelerators (connectors, data flows, orchestrations, utility data model, energy data services, monitoring and reporting dashboards) to speed up the delivery of innovative data driven services and simplify operations. Utilities play a vital role towards achieving the Sustainable Development Goals and now have the opportunity to build universal platforms to facilitate the data economy in a new world including renewable energy. Seamless access to data is crucial to accelerate the digital transformation. -
47
Azure Storage Explorer
Microsoft
Manage your storage accounts in multiple subscriptions across all Azure regions, Azure Stack, and Azure Government. Add new features and capabilities with extensions to manage even more of your cloud storage needs. Accessible, intuitive, and feature-rich graphical user interface (GUI) for full management of cloud storage resources. Securely access your data using Azure AD and fine-tuned access control list (ACL) permissions. Efficiently connect and manage your Azure storage service accounts and resources across subscriptions and organizations. Create, delete, view, edit, and manage resources for Azure Storage, Azure Data Lake Storage, and Azure managed disks. Seamlessly view, search, and interact with your data and resources using an intuitive interface. Improved accessibility with multiple screen reader options, high contrast themes, and hot keys on Windows and macOS. -
48
Dataleyk
Dataleyk
Dataleyk is the secure, fully-managed cloud data platform for SMBs. Our mission is to make Big Data analytics easy and accessible to all. Dataleyk is the missing link in reaching your data-driven goals. Our platform makes it quick and easy to have a stable, flexible and reliable cloud data lake with near-zero technical knowledge. Bring all of your company data from every single source, explore with SQL and visualize with your favorite BI tool or our advanced built-in graphs. Modernize your data warehousing with Dataleyk. Our state-of-the-art cloud data platform is ready to handle your scalable structured and unstructured data. Data is an asset, Dataleyk is a secure, cloud data platform that encrypts all of your data and offers on-demand data warehousing. Zero maintenance, as an objective, may not be easy to achieve. But as an initiative, it can be a driver for significant delivery improvements and transformational results.Starting Price: €0.1 per GB -
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Apache DevLake
Apache Software Foundation
Apache DevLake (Incubating) ingests, analyzes, and visualizes the fragmented data from DevOps tools to distill insights for engineering excellence. Your data lives in many silos and tools. DevLake brings them all together to give you a complete view of your Software Development Life Cycle (SDLC). From DORA to scrum retros, DevLake implements metrics effortlessly with prebuilt dashboards supporting common frameworks and goals. DevLake fits teams of all shapes and sizes, and can be readily extended to support new data sources, metrics, and dashboards, with a flexible framework for data collection and transformation. Select, transform and set up a schedule for the data you wish to sync from your prefered data sources in the config UI. View pre-built dashboards of a variety of use cases and learn engineering insights from the metrics. Customize your own metrics or dashboards with SQL to extend your usage of DevLake.Starting Price: Free -
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Azure Synapse Analytics
Microsoft
Azure Synapse is Azure SQL Data Warehouse evolved. Azure Synapse is a limitless analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless or provisioned resources—at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
