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. Discover watsonx.data Scale AI workloads, for all your data, anywhere See what's coming 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 Download the Forrester report Benefits 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? Enterprise-ready Rely on scale, security, resiliency and flexibility of IBM data lakes that helps run the world’s most mission-critical environments. Innovation 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. Hybrid 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. Foundation watsonx.data 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.