Alternatives to Azure Data Lake Analytics
Compare Azure Data Lake Analytics alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Azure Data Lake Analytics in 2026. Compare features, ratings, user reviews, pricing, and more from Azure Data Lake Analytics 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
MongoDB Atlas
MongoDB
The most innovative cloud database service on the market, with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more. MongoDB Atlas is the global cloud database service for modern applications. Deploy fully managed MongoDB across AWS, Google Cloud, and Azure with best-in-class automation and proven practices that guarantee availability, scalability, and compliance with the most demanding data security and privacy standards. The best way to deploy, run, and scale MongoDB in the cloud. MongoDB Atlas offers built-in security controls for all your data. Enable enterprise-grade features to integrate with your existing security protocols and compliance standards. With MongoDB Atlas, your data is protected with preconfigured security features for authentication, authorization, encryption, and more. -
3
StarTree
StarTree
StarTree, powered by Apache Pinot™, is a fully managed real-time analytics platform built for customer-facing applications that demand instant insights on the freshest data. Unlike traditional data warehouses or OLTP databases—optimized for back-office reporting or transactions—StarTree is engineered for real-time OLAP at true scale, meaning: - Data Volume: query performance sustained at petabyte scale - Ingest Rates: millions of events per second, continuously indexed for freshness - Concurrency: thousands to millions of simultaneous users served with sub-second latency With StarTree, businesses deliver always-fresh insights at interactive speed, enabling applications that personalize, monitor, and act in real time.Starting Price: Free -
4
Fivetran
Fivetran
Fivetran is a leading data integration platform that centralizes an organization’s data from various sources to enable modern data infrastructure and drive innovation. It offers over 700 fully managed connectors to move data automatically, reliably, and securely from SaaS applications, databases, ERPs, and files to data warehouses and lakes. The platform supports real-time data syncs and scalable pipelines that fit evolving business needs. Trusted by global enterprises like Dropbox, JetBlue, and Pfizer, Fivetran helps accelerate analytics, AI workflows, and cloud migrations. It features robust security certifications including SOC 1 & 2, GDPR, HIPAA, and ISO 27001. Fivetran provides an easy-to-use, customizable platform that reduces engineering time and enables faster insights. -
5
Azure Virtual Desktop
Microsoft
Azure Virtual Desktop (formerly Windows Virtual Desktop) is a comprehensive desktop and app virtualization service running in the cloud. It’s the only virtual desktop infrastructure (VDI) that delivers simplified management, multi-session Windows 10, optimizations for Microsoft 365 Apps for enterprise, and support for Remote Desktop Services (RDS) environments. Deploy and scale your Windows desktops and apps on Azure in minutes, and get built-in security and compliance features. Bring your own device (BYOD) and access your desktop and applications over the internet using an Azure Virtual Desktop client such as Windows, Mac, iOS, Android, or HTML5. Choose the right Azure virtual machine (VM) to optimize performance and leverage the Windows 10 and Windows 11 multi-session advantage on Azure to run multiple concurrent user sessions and save costs. -
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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. -
7
Azure HDInsight
Microsoft
Run popular open-source frameworks—including Apache Hadoop, Spark, Hive, Kafka, and more—using Azure HDInsight, a customizable, enterprise-grade service for open-source analytics. Effortlessly process massive amounts of data and get all the benefits of the broad open-source project ecosystem with the global scale of Azure. Easily migrate your big data workloads and processing to the cloud. Open-source projects and clusters are easy to spin up quickly without the need to install hardware or manage infrastructure. Big data clusters reduce costs through autoscaling and pricing tiers that allow you to pay for only what you use. Enterprise-grade security and industry-leading compliance with more than 30 certifications helps protect your data. Optimized components for open-source technologies such as Hadoop and Spark keep you up to date. -
8
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 -
9
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 -
10
Azure Databricks
Microsoft
Unlock insights from all your data and build artificial intelligence (AI) solutions with Azure Databricks, set up your Apache Spark™ environment in minutes, autoscale, and collaborate on shared projects in an interactive workspace. Azure Databricks supports Python, Scala, R, Java, and SQL, as well as data science frameworks and libraries including TensorFlow, PyTorch, and scikit-learn. Azure Databricks provides the latest versions of Apache Spark and allows you to seamlessly integrate with open source libraries. Spin up clusters and build quickly in a fully managed Apache Spark environment with the global scale and availability of Azure. Clusters are set up, configured, and fine-tuned to ensure reliability and performance without the need for monitoring. Take advantage of autoscaling and auto-termination to improve total cost of ownership (TCO). -
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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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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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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 -
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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. -
15
Azure Cosmos DB
Microsoft
Azure Cosmos DB is a fully managed NoSQL database service for modern app development with guaranteed single-digit millisecond response times and 99.999-percent availability backed by SLAs, automatic and instant scalability, and open source APIs for MongoDB and Cassandra. Enjoy fast writes and reads anywhere in the world with turnkey multi-master global distribution. Reduce time to insight by running near-real time analytics and AI on the operational data within your Azure Cosmos DB NoSQL database. Azure Synapse Link for Azure Cosmos DB seamlessly integrates with Azure Synapse Analytics without data movement or diminishing the performance of your operational data store. -
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Trino
Trino
Trino is a query engine that runs at ludicrous speed. Fast-distributed SQL query engine for big data analytics that helps you explore your data universe. Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low-latency analytics. The largest organizations in the world use Trino to query exabyte-scale data lakes and massive data warehouses alike. Supports diverse use cases, ad-hoc analytics at interactive speeds, massive multi-hour batch queries, and high-volume apps that perform sub-second queries. Trino is an ANSI SQL-compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset, and many others. You can natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. Access data from multiple systems within a single query.Starting Price: Free -
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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. -
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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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Actian Analytics Engine
Actian
Actian Analytics Engine is a high-performance analytics database designed to process large volumes of data with speed and efficiency. It uses an in-memory, columnar architecture to enable fast query performance and real-time analytics. The platform supports distributed processing and parallel query execution, allowing users to analyze billions of rows quickly. It incorporates vectorized processing and CPU cache optimization to significantly improve performance. Actian Analytics Engine can ingest data from various sources, including data lakes and external file formats. It provides real-time data updates without performance penalties, ensuring accurate and timely insights. The platform also includes enterprise-grade security features such as encryption and data masking. By combining speed, scalability, and simplicity, it helps organizations make faster, data-driven decisions. -
20
Azure FXT Edge Filer
Microsoft
Create cloud-integrated hybrid storage that works with your existing network-attached storage (NAS) and Azure Blob Storage. This on-premises caching appliance optimizes access to data in your datacenter, in Azure, or across a wide-area network (WAN). A combination of software and hardware, Microsoft Azure FXT Edge Filer delivers high throughput and low latency for hybrid storage infrastructure supporting high-performance computing (HPC) workloads.Scale-out clustering provides non-disruptive NAS performance scaling. Join up to 24 FXT nodes per cluster to scale to millions of IOPS and hundreds of GB/s. When you need performance and scale in file-based workloads, Azure FXT Edge Filer keeps your data on the fastest path to processing resources. Managing data storage is easy with Azure FXT Edge Filer. Shift aging data to Azure Blob Storage to keep it easily accessible with minimal latency. Balance on-premises and cloud storage. -
21
doolytic
doolytic
doolytic is leading the way in big data discovery, the convergence of data discovery, advanced analytics, and big data. doolytic is rallying expert BI users to the revolution in self-service exploration of big data, revealing the data scientist in all of us. doolytic is an enterprise software solution for native discovery on big data. doolytic is based on best-of-breed, scalable, open-source technologies. Lightening performance on billions of records and petabytes of data. Structured, unstructured and real-time data from any source. Sophisticated advanced query capabilities for expert users, Integration with R for advanced and predictive applications. Search, analyze, and visualize data from any format, any source in real-time with the flexibility of Elastic. Leverage the power of Hadoop data lakes with no latency and concurrency issues. doolytic solves common BI problems and enables big data discovery without clumsy and inefficient workarounds. -
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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. -
23
Azure Analysis Services
Microsoft
Use Azure Resource Manager to create and deploy an Azure Analysis Services instance within seconds, and use backup restore to quickly move your existing models to Azure Analysis Services and take advantage of the scale, flexibility and management benefits of the cloud. Scale up, scale down, or pause the service and pay only for what you use. Combine data from multiple sources into a single, trusted BI semantic model that’s easy to understand and use. Enable self-service and data discovery for business users by simplifying the view of data and its underlying structure. Reduce time-to-insights on large and complex datasets. Fast response times mean your BI solution can meet the needs of your business users and keep pace with your business. Connect to real-time operational data using DirectQuery and closely watch the pulse of your business. Visualize your data using your favorite data visualization tool.Starting Price: $0.81 per hour -
24
Azure Data Share
Microsoft
Share data, in any format and any size, from multiple sources with other organizations. Easily control what you share, who receives your data, and the terms of use. Data Share provides full visibility into your data-sharing relationships with a user-friendly interface. Share data in just a few clicks, or build your own application using the REST API. Serverless code-free data-sharing service that requires no infrastructure setup or management. Intuitive interface to govern all your data-sharing relationships. Automated data-sharing processes for productivity and predictability. Secure data-sharing service that uses underlying Azure security measures. Share structured and unstructured data from multiple Azure data stores with other organizations in just a few clicks. There’s no infrastructure to set up or manage, no SAS keys are required, and sharing is all code-free. You control data access and set terms of use aligned with your enterprise policies.Starting Price: $0.05 per dataset-snapshot -
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OpenText Analytics Database is a high-performance, scalable analytics platform that enables organizations to analyze massive data sets quickly and cost-effectively. It supports real-time analytics and in-database machine learning to deliver actionable business insights. The platform can be deployed flexibly across hybrid, multi-cloud, and on-premises environments to optimize infrastructure and reduce total cost of ownership. Its massively parallel processing (MPP) architecture handles complex queries efficiently, regardless of data size. OpenText Analytics Database also features compatibility with data lakehouse architectures, supporting formats like Parquet and ORC. With built-in machine learning and broad language support, it empowers users from SQL experts to Python developers to derive predictive insights.
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26
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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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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Azure Data Science Virtual Machines
Microsoft
DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.Starting Price: $0.005 -
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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. -
31
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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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. -
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Apache Spark
Apache Software Foundation
Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources. -
34
Azure Service Fabric
Microsoft
Focus on building applications and business logic, and let Azure solve the hard distributed systems problems such as reliability, scalability, management, and latency. Service Fabric is an open source project and it powers core Azure infrastructure as well as other Microsoft services such as Skype for Business, Intune, Azure Event Hubs, Azure Data Factory, Azure Cosmos DB, Azure SQL Database, Dynamics 365, and Cortana. Designed to deliver highly available and durable services at cloud-scale, Azure Service Fabric intrinsically understands the available infrastructure and resource needs of applications, enabling automatic scale, rolling upgrades, and self-healing from faults when they occur. Focus on building features that add business value to your application, without the overhead of designing and writing additional code to deal with issues of reliability, scalability, management, or latency in the underlying infrastructure.Starting Price: $0.17 per month -
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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
Hyper-Q
Datometry
Adaptive Data Virtualization™ technology enables enterprises to run their existing applications on modern cloud data warehouses, without rewriting or reconfiguring them. Datometry Hyper-Q™ lets enterprises adopt new cloud databases rapidly, control ongoing operating expenses, and build out analytic capabilities for faster digital transformation. Datometry Hyper-Q virtualization software allows any existing applications to run on any cloud database, making applications and databases interoperable. Enterprises can now adopt the cloud database of choice, without having to rip, rewrite and replace applications. Enables runtime application compatibility with Transformation and Emulation of legacy data warehouse functions. Deploys transparently on Azure, AWS, and GCP clouds. Applications can use existing JDBC, ODBC and Native connectors without changes. Connects to major cloud data warehouses, Azure Synapse Analytics, AWS Redshift, and Google BigQuery. -
37
Microsoft Genomics
Microsoft
Instead of managing your own data centers, take advantage of Microsoft's scale and experience in running exabyte-scale workloads. Because Microsoft Genomics is on Azure, you have the performance and scalability of a world-class supercomputing center, on demand in the cloud. Take advantage of a backend network with MPI latency under three microseconds and non-blocking 32 gigabits per second (Gbps) throughput. This backend network includes remote direct memory access technology that enables parallel applications to scale to thousands of cores. Azure provides you with high memory and HPC-class CPUs to help you get results fast. Scale up and down based on what you need and pay only for what you use to reduce costs. Tackle data sovereignty requirements with a worldwide network of Azure data centers and adhere to your compliance requirements. Easily integrate into your existing pipeline code using a REST-based API and simple Python client. -
38
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. -
39
Azure Disk Storage
Microsoft
Designed to be used with Azure Virtual Machines and Azure VMware Solution (in preview), Azure Disk Storage offers high-performance, durable block storage for your mission- and business-critical applications. Confidently migrate to Azure infrastructure with four disk storage options for the cloud—–Ultra Disk Storage, Premium SSD, Standard SSD, and Standard HDD—to optimize costs and performance for your workload. Get high performance with sub-millisecond latency for throughput and transaction-intensive workloads such as SAP HANA, SQL Server, and Oracle. Run clustered or high-availability applications cost effectively in the cloud using shared disks. Get consistent enterprise-grade durability with a 0% annual failure rate. Meet demand without performance disruption by using Ultra Disk Storage. Secure your data with automatic encryption using Microsoft-managed keys or your own. -
40
Amazon EMR
Amazon
Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data using open-source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. With EMR you can run Petabyte-scale analysis at less than half of the cost of traditional on-premises solutions and over 3x faster than standard Apache Spark. For short-running jobs, you can spin up and spin down clusters and pay per second for the instances used. For long-running workloads, you can create highly available clusters that automatically scale to meet demand. If you have existing on-premises deployments of open-source tools such as Apache Spark and Apache Hive, you can also run EMR clusters on AWS Outposts. Analyze data using open-source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet. Connect to Amazon SageMaker Studio for large-scale model training, analysis, and reporting. -
41
Pragmatic Works
Pragmatic Works
Advance your team and career with the most advanced Power BI, Power Apps, Power Automate, Power Virtual Agents and Azure on-demand and in-person training. Pragmatic Works free community plan gives you lifetime access to 7 Microsoft “in a day” courses on Power BI, Excel, Power Apps, Azure Synapse, Power Automate, Paginated Reports and Chatbots. Master the technology by learning from industry experts, Microsoft MVPs, authors and speakers. 70+ courses on Power BI, Azure, Power Apps and SQL Server, and more. Is your organization moving to a new software or platform, such as Power BI or Power Apps, and all employees are required to be trained on some level? Don’t worry. Our Enterprise Training Plan is here to help with training that leverages the tools to access, learn from and act on data.Starting Price: $195.00/year/user -
42
Veritas NetBackup
Veritas Technologies
Optimized for the multicloud, extensive workload support, and ensured operational resiliency. Ensure data integrity, monitor your environment, and recover at scale to optimize your resilience. Resiliency. Migration. Snapshot orchestration. Disaster recovery. Unified, end-to-end deduplication. One solution manages it all. The most VMs protected, recovered, and moved to the cloud. Protect VMware, Microsoft Hyper-V, Nutanix AHV, Red Hat Virtualization, AzureStack and OpenStack with automated protection and instant access to VM data via flexible recovery. At-scale disaster recovery with near-zero RPO and RTO. Protect your data with 60+ public cloud storage targets, an automated, SLA-driven resiliency platform, and a new supported integration with NetBackup. Get scale-out protection for petabyte-scale workloads with hundreds of data nodes. Use NetBackup Parallel Streaming, a modern parallel streaming agentless architecture. -
43
Kyligence
Kyligence
Let Kyligence Zen take care of collecting, organizing, and analyzing your metrics so you can focus more on taking action Kyligence Zen is the go-to low-code metrics platform to define, collect, and analyze your business metrics. It empowers users to quickly connect their data sources, define their business metrics, uncover hidden insights in minutes, and share them across their organization. Kyligence Enterprise provides diverse solutions based on on-premise, public cloud, and private cloud, helping enterprises of any size to simplify multidimensional analysis based on massive amounts of data according to their business needs. Kyligence Enterprise, based on Apache Kylin, provides sub-second standard SQL query responses based on PB-scale datasets, simplifying multidimensional data analysis on data lakes for enterprises and enabling business users to quickly discover business value in massive amounts of data and drive better business decisions. -
44
Instaclustr
Instaclustr
Instaclustr is the Open Source-as-a-Service company, delivering reliability at scale. We operate an automated, proven, and trusted managed environment, providing database, analytics, search, and messaging. We enable companies to focus internal development and operational resources on building cutting edge customer-facing applications. Instaclustr works with cloud providers including AWS, Heroku, Azure, IBM Cloud, and Google Cloud Platform. The company has SOC 2 certification and provides 24/7 customer support.Starting Price: $20 per node per month -
45
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. -
46
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. -
47
Decision Moments
Mindtree
Mindtree Decision Moments is the first data analytics platform to apply continuous learning algorithms to large data pools. Using this innovative sense-and-respond system, companies can uncover compelling insights that improve over time and create more value from their digital transformation. Decision Moments is an agile and customizable data intelligence platform that simplifies technological complexity by easily adapting to fit the requirements of your organization’s existing data analytics investment. And it’s also flexible enough to modify in response to changes in the market, technologies or business needs. To gain the full value and cost savings of a data analytics platform, Decision Moments is powered by Microsoft Azure services, including the Cortana Intelligence Suite, in a cloud-native solution. Mindtree’s Decision Moments provides your key decision makers with the platform they need to make sense of large amounts of data from multiple sources. -
48
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 -
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Bizintel360
Bizdata
AI powered self-service advanced analytics platform. Connect data sources and derive visualizations without any programming. Cloud native advanced analytics platform that provides high-quality data supply and intelligent real-time analysis across the enterprise without any code. Connect different data sources of different formats. Enables identification of root cause problems. Reduce cycle time: source to target. Analytics without programming knowledge. Real time data refresh on the go. Connect data source of any format, stream data in real time or defined frequency to data lake and visualize them in advanced interactive search engine-based dashboards. Descriptive, predictive and prescriptive analytics in a single platform with the power of search engine and advanced visualization. No traditional technology required to see data in various visualization formats. Roll up, slice and dice data with various mathematical computation right inside Bizintel360 visualization. -
50
Azure Backup
Microsoft
Azure Backup is a cost-effective, secure, one-click backup solution that’s scalable based on your backup storage needs. The centralized management interface makes it easy to define backup policies and protect a wide range of enterprise workloads, including Azure Virtual Machines, SQL and SAP databases, and Azure file shares. Monitor, operate, govern, and optimize data protection at scale in a unified and consistent manner using Backup Center. Back up and restore data from virtual machines with application consistency in Windows using Volume Shadow Copy Service (VSS) and in Linux with pre- and post- processing scripts. Back up Azure Virtual Machines, on-premises servers, SQL Server and SAP HANA on Azure Virtual Machines, Azure Files, and Azure Database for PostgreSQL. Store your backups in locally redundant storage (LRS), geo-redundant storage (GRS), and zone-redundant storage (ZRS). Natively manage your entire backup estate from a central console using Backup Center.Starting Price: $5 per month
