Best Agentic Data Management Platforms for Databricks
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Compare the Top Agentic Data Management Platforms that integrate with Databricks as of October 2026
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This a list of Agentic Data Management platforms that integrate with Databricks. Use the filters on the left to add additional filters for products that have integrations with Databricks. View the products that work with Databricks in the table below.
What are Agentic Data Management Platforms for Databricks?
Agentic data management platforms use autonomous AI agents to manage, govern, and optimize data across complex enterprise environments. They can discover data assets, monitor data quality, and take action to resolve issues such as schema drift, access violations, or pipeline failures. These platforms reason over metadata, usage patterns, and policies to automate decisions that traditionally require human intervention. Many agentic data management platforms integrate with data warehouses, lakes, and analytics tools to operate across the full data lifecycle. By reducing manual effort and improving reliability, they help organizations maintain trusted, scalable, and well-governed data systems. Compare and read user reviews of the best Agentic Data Management platforms for Databricks currently available using the table below. This list is updated regularly.
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1
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. -
2
Ataccama ONE
Ataccama
Ataccama reinvents the way data is managed to create value on an enterprise scale. Unifying Data Governance, Data Quality, and Master Data Management into a single, AI-powered fabric across hybrid and Cloud environments, Ataccama gives your business and data teams the ability to innovate with unprecedented speed while maintaining trust, security, and governance of your data. -
3
Bigeye
Bigeye
Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected. -
4
Anomalo
Anomalo
Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear in your data and before anyone else is impacted. Detect, root-cause, and resolve issues quickly – allowing everyone to feel confident in the data driving your business. Connect Anomalo to your Enterprise Data Warehouse and begin monitoring the tables you care about within minutes. Our advanced machine learning will automatically learn the historical structure and patterns of your data, allowing us to alert you to many issues without the need to create rules or set thresholds. You can also fine-tune and direct our monitoring in a couple of clicks via Anomalo’s No Code UI. Detecting an issue is not enough. Anomalo’s alerts offer rich visualizations and statistical summaries of what’s happening to allow you to quickly understand the magnitude and implications of the problem. -
5
IBM watsonx.data integration is a data integration platform designed to help organizations transform raw data into AI-ready data at scale. The platform enables data teams to build, manage, and optimize data pipelines across multiple environments, including on-premises systems and hybrid or multi-cloud infrastructures. With a unified control plane, watsonx.data integration supports multiple integration styles such as batch processing, real-time streaming, and data replication within a single solution. The platform also offers no-code, low-code, and pro-code development options, allowing both technical and non-technical users to design and manage data pipelines efficiently. By simplifying data integration workflows and reducing reliance on multiple tools, watsonx.data integration helps organizations deliver reliable data for analytics and AI applications.
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6
Acceldata
Acceldata
Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics. -
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Redpanda Agentic Data Plane
Redpanda Data
Redpanda is an enterprise data streaming platform designed to make AI agents safe, governed, and effective across all organizational data. Its Agentic Data Plane connects agents to data sources across cloud, on-prem, and hybrid environments without creating risk or chaos. Redpanda unifies live data streams and historical data into a single, queryable layer. Built-in governance ensures every agent action is authorized, logged, and auditable. The platform enables agents to retrieve exactly the data they need with full context. Redpanda records and replays all agent activity for transparency and debugging. It helps enterprises move from experimental AI to production-ready agentic systems. -
8
Auraa
Covasant Technologies Private Limited
Auraa is Covasant's Databricks-native, agent-driven data platform which is the fastest path to AI-ready data on Databricks. With its conversational AI capabilities in natural language, enterprises can use agents to discover various data sources, build pipelines, enforce data quality, and register everything in Unity Catalog autonomously, from day one. Auraa eliminates pipeline code, engineering backlog, and months of manual configuration. While creation of a data lake on Databricks usually takes more than 18-24 months, Auraa onboards the first source in under 15 minutes, deploys the first use case within hours, and shrinks the overall deployment timeframe to about 8-10 weeks, and reduces the overall implementation cost by upto 70%. Auraa treats every data engineering decision as structured, versioned, governed metadata rather than fragile hand-coded pipelines. Auraa ensures Databricks lakehouse is reproducible, auditable, and continuously improvable by agents. -
9
Kana
Kana
Kana is an agentic marketing platform that helps teams turn fragmented marketing data into real-time decisions and measurable business outcomes. Its applications connect data across the marketing ecosystem, unify information that normally sits in separate tools, and identify patterns, risks, behavioral signals, and opportunities as they emerge. It recommends and executes next-best actions, replacing manual guesswork with data-driven decisions designed to improve performance. Kana’s marketing operating layer sits across tools such as email platforms, ad systems, CRMs, spreadsheets, and other software, using AI agents to coordinate data and actions as one system. Rather than functioning only as generative AI that responds to prompts, its agents can work toward goals, plan multi-step workflows, process signals in real time, and execute actions across the marketing stack.
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