Data lake solutions
Power your applications, analytics, and AI with any data in an open data lakehouse
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Data lake and data lakehouse solutions and IBM

Data lakes and data lakehouses provide a centralized repository for managing large data volumes. They serve as a foundation for collecting and analyzing structured, semi-structured, and unstructured data in its native format for long-term storage and to drive insights and predictions. Unlike traditional data warehouses, they can process video, audio, logs, texts, social media, sensor data, and documents to power apps, analytics, and AI. They can also be built as part of a data fabric architecture to provide the right data, at the right time, regardless of where it is resides.

Hadoop-based data lakes were an attempt to address these new workloads, but required hard-to-find skills for developing applications and managing the platforms. Data lakes are largely being supplanted by a new architectural approach called a data lakehouse.



Scale AI workloads, for all your data, anywhere

How to resolve today’s data challenges with a lakehouse architecture

IBM named a Leader in The Forrester Wave™: Data Management for Analytics, Q1 2023


Scale analytics and AI

Reduce cost and time to insight, and enhance confidence and trust in data used for applications, analytics, and AI with a modern data architecture. Identify new patterns and trends to improve operations and deliver new offerings.

Simplify and make data accessible

Access existing data lakes and data warehouses on-premises or in the cloud, and integrate them with new data to unlock insights and opportunity with a modern data lakehouse and data fabric approach.

Be agile, efficient, and scalable

Deliver business value and reduce data management complexity. Start small and scale across use cases and deployments (cloud, hybrid, and on-premises).

Accelerate time to trusted insights

Control data privacy and security with built-in governance and metadata management. Manage centrally and deploy globally with enterprise-wide governance solutions.

Accelerate deployment and avoid lock-in

Partner with IBM to accelerate deployments across hybrid and multi-cloud environments. Support all types of data and use cases with open source, open standards, and interoperability with IBM and 3rd party services.

Drive down analytics cost

Take advantage of lower cost compute and storage, and fit-for-purpose analytics engines that dynamically scale up and down—pairing the right workload with the right analytic engine.

Why IBM?


Rely on scale, security, resiliency and flexibility of IBM data lakes that helps run the world’s most mission-critical environments.


IBM is trusted to manage the world’s most mission-critical data and applications. Our experience of innovation in enterprise data solutions includes market-making database technology and enterprise ready-AI.


We enable our clients to run our solutions on cloud or in on-premises environments and believe that our client’s data solely belongs to them.


The IBM data lakehouse approach combines the best of IBM with the best of open source. Multi-engine architecture

Optimize warehouse workloads using fit-for-purpose query engines including Presto and Spark that support all data types and workload needs. Modernize data lakes with warehouse-like capabilities.

Consistent metadata layer

Access and share a single copy of data supported by multiple engines and integrated metadata, eliminating duplication and data silos.

Access to all data, anywhere

Deploy anywhere with full support for hybrid-cloud and multi cloud environments.

Data lake solutions

Data lakehouse resources

Learn about a modern solution to distributed data landscapes: the data lakehouse.

Today’s data architecture challenges

The real-world challenges organizations are facing with big data today are multi-faceted.

New strategic approach to analytics

Today's data challenges require a new strategic approach to data management.

Get started

Set up a no-cost, one-on-one call with IBM to explore data lakehouse solutions.

Learn more What is a data lakehouse? What is a data lake? What is a data warehouse What is Hadoop? What is Apache Spark? What is a data mart? What is ETL? What is data management? What is a data fabric?