Alternatives to Lentiq
Compare Lentiq alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Lentiq in 2026. Compare features, ratings, user reviews, pricing, and more from Lentiq competitors and alternatives in order to make an informed decision for your business.
-
1
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
Microsoft Power BI
Microsoft
Power BI is a business intelligence platform that enables users to analyze data using AI-driven tools and intuitive report creation. It consolidates data from various sources into OneLake, creating a centralized data source. This platform aids in embedding actionable insights into applications like Microsoft 365, aiding decision-making. Power BI integrates with Microsoft Fabric, enhancing data management. It offers scalability to handle large data volumes and integrates seamlessly with Microsoft services. Its AI capabilities efficiently identify patterns and generate insights. Power BI ensures data security and compliance. Its Copilot feature allows rapid report generation. Additionally, Power BI Pro offers self-service analytics, and its free version includes data modeling and visualization tools. It's known for unified data management, empowering users with accessibility and training resources. Power BI has demonstrated a significant ROI and economic benefit, as evidenced in a ForresStarting Price: $14/user/month -
3
Composable DataOps Platform
Composable Analytics
Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.Starting Price: $8/hr - pay-as-you-go -
4
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. -
5
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. -
6
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. -
7
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. -
8
Databricks
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
9
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. -
10
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 -
11
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. -
12
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.
-
13
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 -
14
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 -
15
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. -
16
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. -
17
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. -
18
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. -
19
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. -
20
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. -
21
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. -
22
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. -
23
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. -
24
iceDQ
iceDQ
iceDQ is the #1 data reliability platform offering powerful, unified capabilities for Data Testing, Data Monitoring, and Data Observability. Designed for modern data environments, iceDQ automates complex data pipelines and data migration testing to ensure accuracy, integrity, and trust in your data systems. Its AI-based observability engine continuously monitors data in real-time, quickly detecting anomalies and minimizing business risks. With robust cross-platform connectivity, iceDQ supports seamless data validation, data profiling, and data reconciliation across diverse sources — including databases, files, data lakes, SaaS applications, and cloud environments. Whether you're migrating data, ensuring ETL/ELT process quality, or monitoring live data streams, iceDQ helps enterprises deliver high-quality, reliable data at scale. From financial services to healthcare and beyond, organizations rely on iceDQ to make confident, data-driven decisions backed by trusted data pipelines.Starting Price: $1000 -
25
Azure Data Lake
Microsoft
Azure Data Lake includes all the capabilities required to make it easy for developers, data scientists, and analysts to store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. It removes the complexities of ingesting and storing all of your data while making it faster to get up and running with batch, streaming, and interactive analytics. Azure Data Lake works with existing IT investments for identity, management, and security for simplified data management and governance. It also integrates seamlessly with operational stores and data warehouses so you can extend current data applications. We’ve drawn on the experience of working with enterprise customers and running some of the largest scale processing and analytics in the world for Microsoft businesses like Office 365, Xbox Live, Azure, Windows, Bing, and Skype. Azure Data Lake solves many of the productivity and scalability challenges that prevent you from maximizing the -
26
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. -
27
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
-
28
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 -
29
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 -
30
5X
5X
5X is an all-in-one data platform that provides everything you need to centralize, clean, model, and analyze your data. Designed to simplify data management, 5X offers seamless integration with over 500 data sources, ensuring uninterrupted data movement across all your systems with pre-built and custom connectors. The platform encompasses ingestion, warehousing, modeling, orchestration, and business intelligence, all rendered in an easy-to-use interface. 5X supports various data movements, including SaaS apps, databases, ERPs, and files, automatically and securely transferring data to data warehouses and lakes. With enterprise-grade security, 5X encrypts data at the source, identifying personally identifiable information and encrypting data at a column level. The platform is designed to reduce the total cost of ownership by 30% compared to building your own platform, enhancing productivity with a single interface to build end-to-end data pipelines.Starting Price: $350 per month -
31
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. -
32
biGENIUS
biGENIUS AG
biGENIUS automates the entire lifecycle of analytical data management solutions (e.g. data warehouses, data lakes, data marts, real-time analytics, etc.) and thus providing the foundation for turning your data into business as fast and cost-efficient as possible. Save time, efforts and costs to build and maintain your data analytics solutions. Integrate new ideas and data into your data analytics solutions easily. Benefit from new technologies thanks to the metadata-driven approach. Advancing digitalization challenges traditional data warehouse (DWH) and business intelligence systems to leverage an increasing wealth of data. To accommodate today’s business decision making, analytical data management is required to integrate new data sources, support new data formats as well as technologies and deliver effective solutions faster than ever before, ideally with limited resources.Starting Price: 833CHF/seat/month -
33
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. -
34
Cloudera
Cloudera
Manage and secure the data lifecycle from the Edge to AI in any cloud or data center. Operates across all major public clouds and the private cloud with a public cloud experience everywhere. Integrates data management and analytic experiences across the data lifecycle for data anywhere. Delivers security, compliance, migration, and metadata management across all environments. Open source, open integrations, extensible, & open to multiple data stores and compute architectures. Deliver easier, faster, and safer self-service analytics experiences. Provide self-service access to integrated, multi-function analytics on centrally managed and secured business data while deploying a consistent experience anywhere—on premises or in hybrid and multi-cloud. Enjoy consistent data security, governance, lineage, and control, while deploying the powerful, easy-to-use cloud analytics experiences business users require and eliminating their need for shadow IT solutions. -
35
Oracle Big Data Service
Oracle
Oracle Big Data Service makes it easy for customers to deploy Hadoop clusters of all sizes, with VM shapes ranging from 1 OCPU to a dedicated bare metal environment. Customers choose between high-performance NVmE storage or cost-effective block storage, and can grow or shrink their clusters. Quickly create Hadoop-based data lakes to extend or complement customer data warehouses, and ensure that all data is both accessible and managed cost-effectively. Query, visualize and transform data so data scientists can build machine learning models using the included notebook with its R, Python and SQL support. Move customer-managed Hadoop clusters to a fully-managed cloud-based service, reducing management costs and improving resource utilization.Starting Price: $0.1344 per hour -
36
Rapidminer AI Studio
Siemens
RapidMiner AI Studio is a dedicated environment for rapidly developing and prototyping AI solutions, helping teams unify the complete data science lifecycle from data exploration and machine learning to model operations and visualization. It allows data scientists and engineers to build, train, and test AI models locally, giving organizations full control and flexibility for initial exploration and development. It connects directly to enterprise data sources, including files, databases, data lakes, cloud data platforms, warehouses, SQL databases, and Internet of Things data streams, helping teams unify data, prevent errors, and power accurate, explainable AI. RapidMiner AI Studio supports both domain experts and technical teams: users without coding experience can quickly build effective machine learning models with an intuitive drag-and-drop canvas, while data scientists can create complex models in a fully integrated notebook environment using Python and R. -
37
Load your data into or out of Hadoop and data lakes. Prep it so it's ready for reports, visualizations or advanced analytics – all inside the data lakes. And do it all yourself, quickly and easily. Makes it easy to access, transform and manage data stored in Hadoop or data lakes with a web-based interface that reduces training requirements. Built from the ground up to manage big data on Hadoop or in data lakes; not repurposed from existing IT-focused tools. Lets you group multiple directives to run simultaneously or one after the other. Schedule and automate directives using the exposed Public API. Enables you to share and secure directives. Call them from SAS Data Integration Studio, uniting technical and nontechnical user activities. Includes built-in directives – casing, gender and pattern analysis, field extraction, match-merge and cluster-survive. Profiling runs in-parallel on the Hadoop cluster for better performance.
-
38
Deepnote
Deepnote
Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore, and analyze it with real-time collaboration and version control. Users can easily share project links with team collaborators, or with end-users to present polished assets. All of this is done through a powerful, browser-based UI that runs in the cloud. We built Deepnote because data scientists don't work alone. Features: - Sharing notebooks and projects via URL - Inviting others to view, comment and collaborate, with version control - Publishing notebooks with visualizations for presentations - Sharing datasets between projects - Set team permissions to decide who can edit vs view code - Full linux terminal access - Code completion - Automatic python package management - Importing from github - PostgreSQL DB connectionStarting Price: Free -
39
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. -
40
SHREWD Platform
Transforming Systems
Harness your whole system’s data with ease, with our SHREWD Platform tools and open APIs. SHREWD Platform provides the integration and data collection tools the SHREWD modules operate from. The tools aggregate data, storing it in our secure, UK-based data lake. This data is then accessed by the SHREWD modules or an API, to transform the data into meaningful information with targeted functions. Data can be ingested by SHREWD Platform in almost any format, from analog in spreadsheets, to digital systems via APIs. The system’s open API can also allow third-party connections to use the information held in the data lake, if required. SHREWD Platform provides an operational data layer that is a single source of the truth in real-time, allowing the SHREWD modules to provide intelligent insights, and managers and key decision-makers to take the right action at the right time. -
41
Etleap
Etleap
Etleap was built from the ground up on AWS to support Redshift and snowflake data warehouses and S3/Glue data lakes. Their solution simplifies and automates ETL by offering fully-managed ETL-as-a-service. Etleap's data wrangler and modeling tools let users control how data is transformed for analysis, without writing any code. Etleap monitors and maintains data pipelines for availability and completeness, eliminating the need for constant maintenance, and centralizes data from 50+ disparate sources and silos into your data warehouse or data lake. -
42
Lumada IIoT
Hitachi
Embed sensors for IoT use cases and enrich sensor data with control system and environment data. Integrate this in real time with enterprise data and deploy predictive algorithms to discover new insights and harvest your data for meaningful use. Use analytics to predict maintenance problems, understand asset utilization, reduce defects and optimize processes. Harness the power of connected devices to deliver remote monitoring and diagnostics services. Employ IoT Analytics to predict safety hazards and comply with regulations to reduce worksite accidents. Lumada Data Integration: Rapidly build and deploy data pipelines at scale. Integrate data from lakes, warehouses and devices, and orchestrate data flows across all environments. By building ecosystems with customers and business partners in various business areas, we can accelerate digital innovation to create new value for a new society. -
43
Zaloni Arena
Zaloni
End-to-end DataOps built on an agile platform that improves and safeguards your data assets. Arena is the premier augmented data management platform. Our active data catalog enables self-service data enrichment and consumption to quickly control complex data environments. Customizable workflows that increase the accuracy and reliability of every data set. Use machine-learning to identify and align master data assets for better data decisioning. Complete lineage with detailed visualizations alongside masking and tokenization for superior security. We make data management easy. Arena catalogs your data, wherever it is and our extensible connections enable analytics to happen across your preferred tools. Conquer data sprawl challenges: Our software drives business and analytics success while providing the controls and extensibility needed across today’s decentralized, multi-cloud data complexity. -
44
DataOps DataFlow
Datagaps
A holistic component-based platform for automating Data Reconciliation tests in modern Data Lake and Cloud Data Migration projects using Apache Spark. DataOps DataFlow is a modern, web browser-based solution for automating the testing of ETL, Data Warehouse, and Data Migration projects. Use Dataflow to inject data from any of the varied data sources, compare data, and load differences to S3 or a database. With fast and easy to set up, create and run dataflow in minutes. A best in the class testing tool for Big Data Testing DataOps DataFlow can integrate with all modern and advanced data sources including RDBMS, NoSQL, Cloud, and File-Based.Starting Price: Contact us -
45
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. -
46
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 -
47
WhereScape
WhereScape Software
WhereScape helps IT organizations of all sizes leverage automation to design, develop, deploy, and operate data infrastructure faster. More than 700 customers worldwide rely on WhereScape automation to eliminate hand-coding and other repetitive, time-intensive aspects of data infrastructure projects to deliver data warehouses, vaults, lakes and marts in days or weeks rather than in months or years. From data warehouses and vaults to data lakes and marts, deliver data infrastructure and big data integration fast. Quickly and easily plan, model and design all types of data infrastructure projects. Use sophisticated data discovery and profiling capabilities to bulletproof design and rapid prototyping to collaborate earlier with business users. Fast-track the development, deployment and operation of your data infrastructure projects. Dramatically reduce the delivery time, effort, cost and risk of new projects, and better position projects for future business change. -
48
Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2/credit -
49
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 -
50
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
