Alternatives to Databricks
Compare Databricks alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Databricks in 2026. Compare features, ratings, user reviews, pricing, and more from Databricks competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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Couchbase
Couchbase
Couchbase’s operational data platform for AI is a scalable foundation for enterprise operational, analytical, mobile and AI workloads that replaces legacy infrastructure and data services. Bring your data to life in new ways with Couchbase’s enterprise data partnership: launch game-changing customer experiences, explore the infinite possibilities of AI, scale your global operations, and move your data from the cloud to the edge, and beyond. Couchbase’s operational data platform for AI eliminates fragmented tech stacks, so teams can stay innovative and agile, with less risk and lower cost of ownership. With enterprise partnership and scalable, AI-ready technology, Couchbase turns your data into the foundation for your next breakthrough. -
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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. -
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DataHub
DataHub
DataHub Cloud is an event-driven AI & Data Context Platform that uses active metadata for real-time visibility across your entire data ecosystem. Unlike traditional data catalogs that provide outdated snapshots, DataHub Cloud instantly propagates changes, automatically enforces policies, and connects every data source across platforms with 100+ pre-built connectors. Built on an open source foundation with a thriving community of 13,000+ members, DataHub gives you unmatched flexibility to customize and extend without vendor lock-in. DataHub Cloud is a modern metadata platform with REST and GraphQL APIs that optimize performance for complex queries, essential for AI-ready data management and ML lifecycle support. -
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Google Cloud BigQuery
Google
BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process. -
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dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence. -
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Denodo
Denodo Technologies
Denodo is an intelligent data platform that helps organizations deliver live, unified, and governed data for trustworthy AI, analytics, and self-service initiatives. The platform uses logical data management to connect distributed data across hybrid, multi-cloud, on-premises, SaaS, and third-party environments without requiring data movement or duplication. Denodo helps businesses integrate data silos, enable self-service access, enforce governance, deliver real-time insights, and enrich data with business context. It is designed to support agentic AI by giving AI agents accurate, up-to-date, and governed enterprise data for better decisions and actions. The platform includes capabilities such as zero-copy data access, unified semantics, centralized compliance, natural language search, data marketplaces, and optimized query performance. -
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MuleSoft Anypoint Platform
Salesforce
MuleSoft is an agentic control plane designed to help enterprises govern, orchestrate, and secure AI agents, APIs, applications, models, and data across complex digital environments. The platform supports multi-agent governance, API management, integration, automation, and gateway federation from one unified control plane. With solutions such as MuleSoft Agent Fabric, MuleSoft Omni Gateway, Agent Registry, Agent Scanners, and Agent Broker, organizations can discover agents, manage interactions, reduce shadow AI, and coordinate workflows across ecosystems. MuleSoft also helps teams turn existing APIs and applications into governed tools that AI agents can safely discover and use. Its platform supports developers and business users with natural language development, prebuilt connectors, monitoring, API governance, and integration tools. MuleSoft is built to help enterprises scale AI adoption with stronger compliance, observability, security, and operational confidence. -
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Dataiku
Dataiku
Dataiku is an enterprise AI platform designed to help organizations move from fragmented AI efforts to fully scalable and governed AI success. It brings together people, data, and technology into a single system that enables collaboration between domain experts and technical teams. The platform allows users to build, deploy, and manage AI models, analytics workflows, and AI agents with greater efficiency. Dataiku emphasizes orchestration by connecting data sources, applications, and machine learning processes into unified pipelines. It also provides strong governance capabilities, helping organizations monitor performance, control costs, and reduce risks across AI initiatives. Businesses across industries use Dataiku to modernize analytics, automate workflows, and scale machine learning across teams. With proven results from global enterprises, the platform supports faster innovation and measurable ROI through AI-driven solutions. -
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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 -
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Kubit
Kubit
Your data, your insights—no third-party ownership or black-box analytics. Kubit is the leading Customer Journey Analytics platform for enterprises, enabling self-service insights, rapid decisions, and full transparency—without engineering dependencies or vendor lock-in. Unlike traditional tools, Kubit eliminates data silos, letting teams analyze customer behavior directly from Snowflake, BigQuery, or Databricks—no ETL or forced extraction needed. With built-in funnel, path, retention, and cohort analysis, Kubit empowers product teams with fast, exploratory analytics to detect anomalies, surface trends, and drive engagement—without compromise. Enterprises like Paramount, TelevisaUnivision, and Miro trust Kubit for its agility, reliability, and customer-first approach. Learn more at kubit.ai. -
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Rapidminer Monarch
Siemens
Rapidminer Monarch is a Siemens no-code data preparation solution that helps teams clean, transform, and structure data from nearly any source. It allows users to turn information from PDFs, spreadsheets, text reports, databases, and complex files into usable rows and columns for reporting, analytics, machine learning, and other applications. The platform is designed to empower non-technical users to complete data preparation tasks quickly while reducing manual errors. Rapidminer Monarch provides auditable change histories and clear data lineage so teams can trust how data was prepared and transformed. It also supports automated reconciliation workflows, legacy data migration, pre-built apps for business systems, and enterprise deployment through Rapidminer Monarch Server. With drag-and-drop tools, scalable automation, and reliable governance, Rapidminer Monarch helps organizations deliver structured, trusted data faster. -
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Amazon Redshift
Amazon
Amazon Redshift is a cloud-based data warehouse solution from AWS designed to deliver high-performance analytics and support modern AI-driven workloads. The platform enables organizations to analyze large volumes of structured and unstructured data across data warehouses, data lakes, and third-party sources using SQL. Redshift is built for scalability and cost efficiency, offering improved throughput and price-performance with AWS Graviton-powered RG instances and Redshift Serverless options. The solution also supports near real-time analytics through zero-ETL integrations that connect operational databases, streaming services, and enterprise applications without complex data pipelines. Amazon Redshift integrates with Amazon SageMaker and Amazon Bedrock to support advanced machine learning, analytics, and generative AI use cases.Starting Price: $0.543 per hour -
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Amazon SageMaker
Amazon
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers. -
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AWS Glue
Amazon
AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. AWS Glue provides all the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months. Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products. AWS Glue runs in a serverless environment. There is no infrastructure to manage, and AWS Glue provisions, configures, and scales the resources required to run your data integration jobs. -
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Alation
Alation
The Alation Agentic Data Intelligence Platform enables organizations to scale and accelerate their AI and data initiatives. By unifying search, cataloging, governance, lineage, and analytics, it transforms metadata into a strategic asset for decision-making. The platform’s AI-powered agents—including Documentation, Data Quality, and Data Products Builder—automate complex data management tasks. With active metadata, workflow automation, and more than 120 pre-built connectors, Alation integrates seamlessly into modern enterprise environments. It helps organizations build trusted AI models by ensuring data quality, transparency, and compliance across the business. Trusted by 40% of the Fortune 100, Alation empowers teams to make faster, more confident decisions with trusted data. -
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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 -
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MarkLogic
Progress Software
Unlock data value, accelerate insightful decisions, and securely achieve data agility with the MarkLogic data platform. Combine your data with everything known about it (metadata) in a single service and reveal smarter decisions—faster. Get a faster, trusted way to securely connect data and metadata, create and interpret meaning, and consume high-quality contextualized data across the enterprise with the MarkLogic data platform. Know your customers in-the-moment and provide relevant and seamless experiences, reveal new insights to accelerate innovation, and easily enable governed access and compliance with a single data platform. MarkLogic provides a proven foundation to help you achieve your key business and technical outcomes—now and in the future. -
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Palantir AIP
Palantir
Deploy LLMs and other AI — commercial, homegrown or open-source — on your private network, based on an AI-optimized data foundation. AI Core is a real-time, full-fidelity representation of your business that includes all actions, decisions, and processes. Utilize the Action Graph, atop the AI Core, to set specific scopes of activity for LLMs and other models – including hand-off procedures for auditable calculations and human-in-the-loop operations. Monitor and control LLM activity and reach in real-time to help users promote compliance with legal, data sensitivity, and regulatory audit requirements. -
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Palantir Foundry
Palantir Technologies
Foundry is a transformative data platform built to help solve the modern enterprise’s most critical problems by creating a central operating system for an organization’s data, while securely integrating siloed data sources into a common analytics and operations picture. Palantir works with commercial companies and government organizations alike to close the operational loop, feeding real-time data into your data science models and updating source systems. With a breadth of industry-leading capabilities, Palantir can help enterprises traverse and operationalize data to enable and scale decision-making, alongside best-in-class security, data protection, and governance. Foundry was named by Forrester as a leader in the The Forrester Wave™: AI/ML Platforms, Q3 2022. Scoring the highest marks possible in product vision, performance, market approach, and applications criteria. As a Dresner-Award winning platform, Foundry is the overall leader in the BI and Analytics market and rate -
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Palantir Gotham
Palantir Technologies
Integrate, manage, secure, and analyze all of your enterprise data. Organizations have data. Lots of it. Structured data like log files, spreadsheets, and tables. Unstructured data like emails, documents, images, and videos. This data is typically stored in disconnected systems, where it rapidly diversifies in type, increases in volume, and becomes more difficult to use every day. The people who rely on this data don't think in terms of rows, columns, or raw text. They think in terms of their organization's mission and the challenges they face. They need a way to ask questions about their data and receive answers in a language they understand. Enter the Palantir Gotham Platform. Palantir Gotham integrates and transforms data, regardless of type or volume, into a single, coherent data asset. As data flows into the platform, it is enriched and mapped into meaningfully defined objects — people, places, things, and events — and the relationships that connect them. -
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Mistral OCR 4
Mistral AI
Mistral OCR 4 is a document extraction and understanding model built for enterprise search, RAG, domain-specific retrieval pipelines, and production-grade document intelligence. It extracts and structures content from a wide range of documents, moving beyond clean text and tables to return a structured representation of each page. Alongside extracted text, OCR 4 provides bounding boxes, typed-block classification, and inline confidence scores, helping downstream systems understand not only what the document says, but where each element sits, what role it plays, and how confident the model is in each region. Bounding boxes make in-context highlighting and reliable data pipelines possible, while block types and confidence scores support source-grounded citations, redactions, and human-in-the-loop verification. OCR 4 accepts common enterprise formats, including PDF, DOC, PPT, and OpenDocument, and supports 170 languages across 10 language groups.Starting Price: $2 per 1000 pages -
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Microsoft Foundry
Microsoft
Microsoft Foundry is an end-to-end platform for building, optimizing, and governing AI apps and agents at scale. It gives developers access to more than 11,000 models — from foundational to multimodal — all available through one unified interface. With a simple, interoperable API and SDK, teams can build faster, ship confidently, and reduce integration complexity. Foundry connects seamlessly with your business systems, enabling AI solutions that understand your data and operate securely across your organization. Built-in governance, monitoring, and fleetwide controls ensure responsible AI deployment from day one. Microsoft Foundry helps companies turn AI into real business impact with speed, security, and precision. -
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Onehouse
Onehouse
The only fully managed cloud data lakehouse designed to ingest from all your data sources in minutes and support all your query engines at scale, for a fraction of the cost. Ingest from databases and event streams at TB-scale in near real-time, with the simplicity of fully managed pipelines. Query your data with any engine, and support all your use cases including BI, real-time analytics, and AI/ML. Cut your costs by 50% or more compared to cloud data warehouses and ETL tools with simple usage-based pricing. Deploy in minutes without engineering overhead with a fully managed, highly optimized cloud service. Unify your data in a single source of truth and eliminate the need to copy data across data warehouses and lakes. Use the right table format for the job, with omnidirectional interoperability between Apache Hudi, Apache Iceberg, and Delta Lake. Quickly configure managed pipelines for database CDC and streaming ingestion. -
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Matillion
Matillion
Cloud-Native ETL Tool. Load and Transform Data To Your Cloud Data Warehouse In Minutes. We reversed the traditional ETL process to create a solution that performs data integration within the cloud itself. Our solution utilizes the near-infinite storage capacity of the cloud—meaning your projects get near-infinite scalability. By working in the cloud, we reduce the complexity involved in moving large amounts of data. Process a billion rows of data in fifteen minutes—and go from launch to live in just five. Modern businesses seeking a competitive advantage must harness their data to gain better business insights. Matillion enables your data journey by extracting, migrating and transforming your data in the cloud allowing you to gain new insights and make better business decisions. -
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SAS Enterprise Miner
SAS Institute
Streamline the data mining process to develop models quickly. Understand key relationships. And find the patterns that matter most. Dramatically shorten model development time for your data miners and statisticians. An interactive, self-documenting process flow diagram environment efficiently maps the entire data mining process to produce the best results. And it has more predictive modeling techniques than any other commercial data mining package. Why not use the best? Business users and subject-matter experts with limited statistical skills can generate their own models using SAS Rapid Predictive Modeler. An easy-to-use GUI steps them through a workflow of data mining tasks. Analytics results are displayed in easy-to-understand charts that provide the insights needed for better decision-making. Create better-performing models using innovative algorithms and industry-specific methods. Verify results with visual assessment and validation metrics. -
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SAS Viya
SAS
SAS Viya is a cloud-native data and AI platform that unifies data management, analytics, AI modeling, and governance within a single environment. The platform helps organizations build, validate, deploy, and govern AI models with transparency, fairness, and auditability built into the entire lifecycle. SAS Viya provides seamless access to data across multiple sources and platforms while maintaining governance, lineage tracking, and compliance controls. Businesses can use the platform to accelerate AI model training, improve workflow productivity, and operationalize data-driven decisions at scale. SAS Viya also supports AI agents through the SAS Viya MCP Server, enabling secure integration of AI-powered tools and decision-making processes. The platform is designed to support cloud, hybrid, and on-premises deployments for greater flexibility across enterprise environments. -
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RazorThink
RazorThink
RZT aiOS offers all of the benefits of a unified artificial intelligence platform and more, because it's not just a platform — it's a comprehensive Operating System that fully connects, manages and unifies all of your AI initiatives. And, AI developers now can do in days what used to take them months, because aiOS process management dramatically increases the productivity of AI teams. This Operating System offers an intuitive environment for AI development, letting you visually build models, explore data, create processing pipelines, run experiments, and view analytics. What's more is that you can do it all even without advanced software engineering skills. -
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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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Stackable
Stackable
The Stackable data platform was designed with openness and flexibility in mind. It provides you with a curated selection of the best open source data apps like Apache Kafka, OpenSearch, Trino, and Apache Spark. While other current offerings either push their proprietary solutions or deepen vendor lock-in, Stackable takes a different approach. All data apps work together seamlessly and can be added or removed in no time. Based on Kubernetes, it runs everywhere, on-prem or in the cloud. stackablectl and a Kubernetes cluster are all you need to run your first stackable data platform. Within minutes, you will be ready to start working with your data. Configure your one-line startup command right here. Similar to kubectl, stackablectl is designed to easily interface with the Stackable Data Platform. Use the command line utility to deploy and manage stackable data apps on Kubernetes. With stackablectl, you can create, delete, and update components.Starting Price: Free -
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Starburst Enterprise
Starburst Data
Starburst helps you make better decisions with fast access to all your data; Without the complexity of data movement and copies. Your company has more data than ever before, but your data teams are stuck waiting to analyze it. Starburst unlocks access to data where it lives, no data movement required, giving your teams fast & accurate access to more data for analysis. Starburst Enterprise is a fully supported, production-tested and enterprise-grade distribution of open source Trino (formerly Presto® SQL). It improves performance and security while making it easy to deploy, connect, and manage your Trino environment. Through connecting to any source of data – whether it’s located on-premise, in the cloud, or across a hybrid cloud environment – Starburst lets your team use the analytics tools they already know & love while accessing data that lives anywhere. -
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Salesforce Data 360
Salesforce
Data 360 is Salesforce’s next-generation data platform, evolving from Data Cloud to unify and activate enterprise data in real time. It connects fragmented data across systems into a single, trusted Customer 360 view without requiring data movement. Through Zero-Copy integrations, Data 360 works directly with platforms like Snowflake, Databricks, BigQuery, and AWS. The platform harmonizes structured and unstructured data to power personalized experiences and intelligent workflows. Built-in identity resolution and governance tools ensure data accuracy, compliance, and privacy. Data 360 enables real-time segmentation, predictive insights, and triggered automation across Salesforce and external applications. It serves as the data foundation for Agentforce, delivering context-rich intelligence to AI agents and business teams. -
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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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SAP Datasphere
SAP
SAP Datasphere is a unified data experience platform within SAP Business Data Cloud, designed to provide seamless, scalable access to mission-critical business data. It integrates data from SAP and non-SAP systems, harmonizing diverse data landscapes and enabling faster, more accurate decision-making. With capabilities like data federation, cataloging, semantic modeling, and real-time data integration, SAP Datasphere ensures that businesses have consistent, contextualized data across hybrid and cloud environments. The platform simplifies data management by preserving business context and logic, providing a comprehensive view of data that drives innovation and enhances business processes. -
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Saturn Cloud
Saturn Cloud
Saturn Cloud is an AI/ML platform available on every cloud. Data teams and engineers can build, scale, and deploy their AI/ML applications with any stack. Quickly spin up environments to test new ideas, then easily deploy them into production. Scale fast—from proof-of-concept to production-ready applications. Customers include NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. Get started for free at: saturncloud.ioStarting Price: $0.005 per GB per hour -
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SQream
SQream
SQream is a GPU-accelerated data analytics platform that enables organizations to process large, complex datasets with unprecedented speed and efficiency. By leveraging NVIDIA's GPU technology, SQream executes intricate SQL queries on vast datasets rapidly, transforming hours-long processes into minutes. It offers dynamic scalability, allowing businesses to seamlessly scale their data operations in line with growth, without disrupting analytics workflows. SQream's architecture supports deployments that provide flexibility to meet diverse infrastructure needs. Designed for industries such as telecom, manufacturing, finance, advertising, and retail, SQream empowers data teams to gain deep insights, foster data democratization, and drive innovation, all while significantly reducing costs. -
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Tecton
Tecton
Deploy machine learning applications to production in minutes, rather than months. Automate the transformation of raw data, generate training data sets, and serve features for online inference at scale. Save months of work by replacing bespoke data pipelines with robust pipelines that are created, orchestrated and maintained automatically. Increase your team’s efficiency by sharing features across the organization and standardize all of your machine learning data workflows in one platform. Serve features in production at extreme scale with the confidence that systems will always be up and running. Tecton meets strict security and compliance standards. Tecton is not a database or a processing engine. It plugs into and orchestrates on top of your existing storage and processing infrastructure. -
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Snowflake Cortex AI
Snowflake
Snowflake Cortex AI is a fully managed, serverless platform that enables organizations to analyze unstructured data and build generative AI applications within the Snowflake ecosystem. It offers access to industry-leading large language models (LLMs) such as Meta's Llama 3 and 4, Mistral, and Reka-Core, facilitating tasks like text summarization, sentiment analysis, translation, and question answering. Cortex AI supports Retrieval-Augmented Generation (RAG) and text-to-SQL functionalities, allowing users to query structured and unstructured data seamlessly. Key features include Cortex Analyst, which enables business users to interact with data using natural language; Cortex Search, a hybrid vector and keyword search engine for document retrieval; and Cortex Fine-Tuning, which allows customization of LLMs for specific use cases.Starting Price: $2 per month -
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TrueFoundry
TrueFoundry
TrueFoundry is a unified platform with an enterprise-grade AI Gateway - combining LLM, MCP, and Agent Gateway - to securely manage, route, and govern AI workloads across providers. Its agentic deployment platform also enables GPU-based LLM deployment along with agent deployment with best practices for scalability and efficiency. It supports on-premise and VPC installations while maintaining full compliance with SOC 2, HIPAA, and ITAR standards.Starting Price: $5 per month -
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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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IOMETE
IOMETE
IOMETE is a self-hosted data lakehouse platform built on Apache Iceberg, Apache Spark, and Kubernetes. Run it on-premises or in your private cloud — your infrastructure, your data, your control. Built for enterprises in regulated industries, IOMETE eliminates third-party ICT risk at the data layer by architecture — not by contract. No SaaS dependencies. No data leaving your perimeter. Compliance with GDPR, DORA, and NIS2 is structural, not contractual. Included in one platform: - Data Lakehouse(s) - Data Catalog - SQL Editor - Apache Spark Jobs - ML Notebooks - Orchestration Engine - Spark Connect Key capabilities: Apache Iceberg-native storage, Kubernetes-native deployment (K8s + OpenShift), row/column/tag-based access control, Data Mesh support, air-gapped and zero-trust compatible. Transparent pricing — CPU-based, no per-query fees, no billing surprises.Starting Price: Free -
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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. -
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Apache Zeppelin
Apache
Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala and more. IPython interpreter provides comparable user experience like Jupyter Notebook. This release includes Note level dynamic form, note revision comparator and ability to run paragraph sequentially, instead of simultaneous paragraph execution in previous releases. Interpreter lifecycle manager automatically terminate interpreter process on idle timeout. So resources are released when they're not in use. -
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Amazon Athena
Amazon
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified metadata repository across various services, crawl data sources to discover schemas and populate your Catalog with new and modified table and partition definitions, and maintain schema versioning. -
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Amazon DataZone
Amazon
Amazon DataZone is a data management service that enables customers to catalog, discover, share, and govern data stored across AWS, on-premises, and third-party sources. It allows administrators and data stewards to manage and control access to data using fine-grained controls, ensuring that users have the appropriate level of privileges and context. The service simplifies data access for engineers, data scientists, product managers, analysts, and business users, facilitating data-driven insights through seamless collaboration. Key features of Amazon DataZone include a business data catalog for searching and requesting access to published data, project collaboration tools for managing and monitoring data assets, a web-based portal providing personalized views for data analytics, and governed data sharing workflows to ensure appropriate data access. Additionally, Amazon DataZone automates data discovery and cataloging using machine learning. -
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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. -
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Anyscale
Anyscale
Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. Deployment options are flexible, supporting public clouds, on-premises clusters, and Kubernetes environments. Anyscale Jobs and Services enable reliable production-grade batch processing and scalable web services with features like job queuing, retries, observability, and zero-downtime upgrades. Security and compliance are ensured with private data environments, auditing, access controls, and SOC 2 Type II attestation.Starting Price: $0.00006 per minute -
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Apache Airflow
The Apache Software Foundation
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows. -
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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 -
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Cloud Dataprep
Google
Cloud Dataprep by Trifacta is an intelligent data service for visually exploring, cleaning, and preparing structured and unstructured data for analysis, reporting, and machine learning. Because Cloud Dataprep is serverless and works at any scale, there is no infrastructure to deploy or manage. Your next ideal data transformation is suggested and predicted with each UI input, so you don’t have to write code. Cloud Dataprep is an integrated partner service operated by Trifacta and based on their industry-leading data preparation solution. Google works closely with Trifacta to provide a seamless user experience that removes the need for up-front software installation, separate licensing costs, or ongoing operational overhead. Cloud Dataprep is fully managed and scales on demand to meet your growing data preparation needs so you can stay focused on analysis.
