IBM watsonx.data is an open, hybrid data foundation that helps organizations connect, understand, govern and optimize real-time AI-ready data across hybrid environments
Overview
Make your data AI-ready—connected, governed, and context-rich
AI is only as reliable as the data behind it. But enterprise data is often fragmented across clouds, applications, data warehouses, documents, streaming systems and on-premises environments. Without access to data across systems , business context, and governance, AI outputs can be incomplete, inconsistent or difficult to defend.
IBM watsonx.data helps organizations turn distributed data into AI-ready context. It connects data where it lives, enriches it with business meaning, and applies governance, lineage and access controls across AI and analytics workloads—so teams can move from pilots to production with greater confidence.
Features
Designed to deliver trustworthy, AI-ready data at scale
Access, query and govern data across cloud, multicloud, SaaS, client-managed VPC and on-premises environments. Deploy as SaaS for speed, self-managed software for control, or BYOC to balance managed operations with your security, sovereignty and compliance requirements.
With watsonx.data, teams can bring compute and context to distributed data—reducing unnecessary movement, duplication and replatforming while supporting regulatory, latency and operational needs.
Optimize AI, BI, analytical, and operational workloads with a multi-engine architecture built on open technologies. Use fit-for-purpose engines to improve performance, avoid overprovisioning and keep costs predictable as data and AI usage scale.
- Presto: Distributed SQL engine for interactive BI reporting and analytics, with high-performance query processing and federation. Check out our GPU-accelerated Presto Technical Preview!
- Spark: Unified analytics engine for distributed data processing, accelerating data engineering, large scale model training, and advanced AI/ML pipeline execution
- OpenSearch: Unified vector + keyword search for accurate, context-aware retrieval for GenAI and search applications
- Cassandra: Cassandra-based distributed noSQL engine for fast read/write and linear scaling for fast, responsible GenAI and web/mobile applications.
Apply consistent governance, access controls, policies, lineage and data quality signals across distributed data and workloads. Watsonx.data helps ensure AI systems and analytics users access the right data, under the right policies, at the moment it is used.
Governance is built in—not bolted on—so teams can scale AI with greater confidence, transparency and control.
Build on an open data foundation with open-source engines, open formats and open standards. Watsonx.data helps teams maximize existing investments, avoid redundant copies, and interoperate with the tools, clouds and platforms already in their data estate.
Use open standards, zero-copy data access and open ecosystem integrations to support new AI and analytics workloads without locking data into a single vendor architecture or forcing migration.
See how AI-ready data becomes real-time context
Explore how watsonx.data helps teams connect distributed data, enrich it with business meaning, and govern it for trusted AI and analytics. Start with a focused use case—enterprise knowledge, real-time AI applications, workload optimization or governed analytics—then scale across your hybrid data estate.
Use cases
Unlock value from your data
Use the OpenRAG on watsonx.data capability to ground AI agents and applications in governed enterprise knowledge. Combine document processing, hybrid search, agentic retrieval and orchestration to move beyond rigid, vector-only RAG pipelines and deliver more context-aware AI outcomes in minutes.
Connect and enrich real-time operational data to power low-latency applications, AI, and analytics using current business context—not stale snapshots. Enable AI applications to deliver reliable and explainable results.
Run each workload on the engine best suited to its needs. Watsonx.data supports AI, BI, analytics, and operational workloads with a fit-for-purpose, multi-engine architecture—helping teams improve performance, reduce duplication and better control cost as usage grows.
Case studies
Real clients, real results
Resolving help desk tickets faster with AI-ready data
CrushBank increased its tickets resolved per day by 40%, using watsonx.data as a central, governed store for structured and unstructured data. This enabled their AI system to retrieve accurate, customer-specific information quickly, cutting average resolution time and improving first-call resolution rates.
Resources
Insights and supporting materials
Explore videos, client stories, product documentation, analyst reports and more that helps Data Leaders maximize their data for reliable AI outputs.
Pricing
Ways to buy
IBM watsonx.data pricing is designed to be flexible and scalable, enabling organizations of all sizes to optimize costs while managing growing data workloads.
Use cloud credits
Footnotes
1. Millions Lost In 2023 Due To Poor Data Quality, Potential For Billions To Be Lost With AI Without Intervention, Forrester, 31 July 2024.