As part of CRN’s 2026 AI 100 list, here are 15 big data companies that manage the flow of data for automated AI applications and agentic systems.
As AI systems and applications proliferate, their need for data—lots of it—to complete their tasks is growing exponentially. AI agents, for example, require instant access to current, accurate data in order to effectively make autonomous decisions.
Data management technology developers—and the solution providers they work with—play a key role in helping organizations collect, integrate, prepare and manage data for AI and agentic applications and the models that power them.
“What’s really driving this is the proliferation of AI agents,” said Craig Wiley, vice president of AI and product at fast-growing data and AI platform provider Databricks, in a recent interview with CRN.
Solution providers, Wiley said, are increasingly called on to work with their customers to develop a unified system of governance that oversees the data AI agents are tapping into and the autonomous actions agents take based on that data.
Data analytics software companies, meanwhile, are racing to build AI capabilities into their offerings, including AI agents and natural language querying functionality, that make sophisticated data analysis possible for everyday business users.
Data analytics leader ThoughtSpot, for example, recently launched Spotter for Industries, an extension of its Spotter agentic analytics platform that will help eliminate what CEO Ketan Karkhanis calls “the context gap”—the inability of first-generation AI agents to work effectively because they don’t understand the lexicon and jargon of vertical industries.
“We are not shipping technology, we’re shipping industry solutions,” Karkhanis said in an interview with CRN. “Industry solutions don’t talk SQL, they talk industry language and industry vernacular. We’re giving our customers a faster path to going live with industry solutions.”
As part of CRN’s 2026 AI 100 list here are 15 big data companies, including providers of data analytics software, database systems, data management platforms, data integration and transformation tools, data governance software, data warehouse and lakehouse systems, and other technologies that manage the flow of data for automated AI applications and agentic systems.
Airbyte
Michel Tricot
Co-Founder, CEO
Airbyte’s data replication and integration platform plays a critical role in preparing and managing governed data for AI systems and agents and the models that power them. That includes supplying data for training large language models, integrating data into operational and analytical AI systems, and connecting data sources to vector databases for AI applications.
In February the San Francisco-based company launched the public beta of Airbyte Agent Engine, a unified interface for AI agents to external data sources.
Alteryx
Andy MacMillan
CEO
Alteryx positions its Alteryx One as an “AI data clearinghouse,” providing a unified, multifunction platform for preparing data and managing data flows for a broad range of automated AI applications and agentic systems.
Alteryx One, according to the Irvine, Calif.-based company, democratizes AI-powered analytics for partners and business users by automating analytics and AI workflows, preparing and governing data for AI applications and agents, integrating generative AI for analytical insight and reports, and providing real-time data access for AI models.
Couchbase
BJ Schaknowski
CEO
Next-generation database provider Couchbase positions itself as a data enabler for AI and agentic applications by building AI services directly into its database platform, including its popular Capella cloud database. The San Jose, Calif.-based company’s Couchbase AI Services, launched in December, is a comprehensive suite of capabilities—such as model hosting, automatic vector creation, a unified agent catalog and integration with Nvidia AI Enterprise—for building, deploying and governing custom agentic AI applications.
Databricks
Ali Ghodsi
Co-Founder, CEO
Databricks has become one of the leading IT companies in the data and AI space and in February said it had surpassed a $1.4 billion annual revenue run rate just for its AI products.
Databricks’ flagship Data Intelligence Platform incorporates the San Francisco-based company’s core data and AI offerings, including the Lakebase database designed for AI agents, Lakeflow Designer for building data pipelines, and the Agent Bricks production-scale AI agent development workspace. The company recently introduced Genie Code, an autonomous AI agent that assists with data engineering, data science and analytics tasks.
In addition, Databricks and Accenture just launched the Accenture Databricks Business Group, a joint venture with 25,000 Databricks-trained professionals, with the goal of accelerating AI development on the Databricks platform.
Dataiku
Florian Douetteau
Co-Founder, CEO
Dataiku provides an AI and machine learning platform that allows technical experts and business analysts to prepare, build and deploy AI models and agents. The most recent evolution, the Platform for AI Success, helps organizations move beyond pilot projects and scale up trusted, governed AI “with real business results.” Kiji Inspector, the New York-based company’s most recent offering, is an open-source tool for extending explainability, transparency and governance to enterprise AI agents.
Dbt Labs
Tristan Handy
Founder, CEO
AI applications and agents need clean, trusted, well-formatted data to do their jobs. The Dbt Labs command line tool, powered by the Dbt Fusion Engine, enables data analysts and engineers to quickly transform data within their data warehouses for complex AI and analytical tasks.
The Philadelphia-based company is in the process of merging with Fivetran, a developer of automated data movement technology used to centralize data from SaaS applications, databases and other sources. The Dbt Labs-FiveTran combination will create an AI data infrastructure powerhouse with annual recurring revenue nearing $600 million.
Domino Data Lab
Nick Elprin
Co-Founder, CEO
Domino Data Lab offers a unified AI and data science system for building, deploying and managing AI models more quickly, at scale. The San Francisco-based company’s Domino Enterprise AI Platform provides a unified development workspace, a collaborative central repository for projects and models, and governance and compliance capabilities.
A major update of the platform in February provided a new agentic development life-cycle experience and new underlying LLM hosting capabilities—all for building, evaluating, deploying and monitoring agentic AI systems at scale with built-in governance, reproducibility and control.
EDB
Kevin Dallas
CEO
EDB develops a PostgresSQL-based relational database and in recent years has focused on developing its flagship product, EDB Postgres AI, as a comprehensive platform for analytical tasks and agentic AI applications. More recently the Wilmington, Del.-based company has been emphasizing the role of its database as an enterprise-grade “sovereign” data and AI platform that helps organizations control where data resides, how AI is governed, and where intelligent systems are deployed.
EDB just unveiled expanded integrations with Nvidia cuDF for Apache Spark, a move that accelerates the use of Postgres on Nvidia AI infrastructure and improves agentic AI performance.
Ocient
John Morris
CEO
Ocient’s hyperscale data warehouse and analytics system is capable of ingesting, organizing and analyzing complex, petabyte-scale datasets, providing the data infrastructure for real-time AI agentic and autonomous AI system workloads.
The Chicago-based company’s solution provider and partners—including Carahsoft, CBTS, Insight Enterprise/SADA, TenX, Trace3 and Vertosoft—leverage the Ocient system to operationalize AI, including unifying data for AI agents and running agentic workloads at scale, for customers in the telecommunications and financial services industries, federal government agencies and others.
Pinecone
Ash Ashutosh
CEO
Pinecone develops an industry-leading vector database that has become a key component within many production-scale AI workloads. Key to the New York-based company’s success is its ability to efficiently store and query billions of “vectors,” numerical representations of complex data such as text, images, video and audio generated by AI models.
Ashutosh, previously Google global director of solution sales, was named the company’s CEO in September with founder Edo Liberty becoming chief scientist.
Qlik
Mike Capone
CEO
Qlik is a leading software developer in the business intelligence and data analytics space and in recent years has also become a major provider of data integration tools for data replication, data organization, building data lakes and data warehouses, and maintaining data quality and integrity. The King of Prussia, Pa.-based company’s AI offerings enable AI-powered analytics, natural language capabilities and visualizations.
In February Qlik announced the general availability of agentic analytics capabilities within its Qlik Cloud platform, delivered through the Qlik Answers conversational interface, and an MCP server that extends Qlik’s data intelligence into AI assistants.
SAS
Jim Goodnight
Co-Founder, CEO
SAS is a longtime leader in data analytics, data governance, machine learning and model development and has leveraged its technology to become a major player in the current wave of generative AI and AI agents.
As was true with its analytics offerings, the Cary, N.C.-based company has been particularly successful in developing industry-specific AI solutions for banking, insurance, health care, life sciences, manufacturing, retail and the public sector. Providing AI for managing risk and preventing fraud in financial services is a leading example.
Starburst
Justin Borgman
Co-Founder, CEO
Starburst describes its federated data platform as “the missing layer between data and AI,” providing AI agents and applications—across cloud and on-premises systems—with the governed data access, context and tools they need for trusted AI outcomes.
At the core of the Boston-based company’s AI strategy is the Starburst data lakehouse platform with added capabilities “designed to operationalize the agentic workforce,” according to the company. Those include built-in support for model-to-data architectures, multi-agent interoperability, and an open vector store built on the Iceberg table standard.
Teradata
Steve McMillan
President, CEO
Data warehouse pioneer Teradata is a force in the AI data space with its AI Factory platform, a secure on-premises system for building, deploying and managing AI workloads while meeting data governance, privacy and compliance requirements. The AI factory, built on Nvidia GPUs and Teradata’s ClearScape Analytics, AI Workbench and AI microservices, is designed for use within regulated industries and by organizations that require complete control over enterprise data.
The San Diego-based company is currently offering a public preview of its Teradata AI Unlimited cloud-based AI/machine learning engine.
ThoughtSpot
Ketan Karkhanis
CEO
ThoughtSpot was already among the top business intelligence and data analytics tech developers before the AI wave. ThoughtSpot has since moved quickly to build AI agent technology into its portfolio to boost the capabilities of its products and make them easier to use by everyday business users.
The Mountain View, Calif.-based company launched its Spotter AI agentic analysis platform in late 2024 and in December 2025 debuted a suite of business intelligence agents to assist data teams as they build data analytics workflows. And the just-launched Spotter for Industries will, according to CEO Karkhanis, help channel partners develop agentic analysis solutions for customers in vertical markets.
