Feature spotlights
Deep integration into the Hadoop ecosystem
Exploit Hive, Hbase and Spark using a single database connection. Whether on the cloud, on premises or both, access data across Hadoop and relational databases.
Advanced cost-based optimizer and massive parallel processing (MPP)
Run smarter queries supporting more concurrent users with less hardware compared to other SQL solutions for Hadoop. Run all 99 TPCDS queries up to 100 TB with numerous concurrent users. Provides an ANSI-compliant SQL parser to run queries from unstructured streaming data using new APIs.
Data science-ready
Build, train, deploy and manage AI models, and prepare and analyze data for machine learning in a single, integrated environment. Integrate with Apache Spark for easier data delivery and faster processing.
SQL compatible with other vendors, products and dialects
Integrate with Oracle, the IBM Db2® product family, including the IBM Db2 AI database, and IBM Netezza® and provide federated access to relational database management system (RDBMS) sources outside of Hadoop with IBM Fluid Query. Connect to HDFS, RDBMS, NoSQL databases, object stores and Web HDFS.
Hybrid flex
IBM Hybrid Data Management Platform allows you to leverage all available data, no matter the type, source or structure. Simply purchase IBM FlexPoints and allocate towards multiple resources with a single, subscription-based license.
User-friendly, familiar SQL interface and tools
Based on standard compliant open database connectivity (ODBC) and Java database connectivity (JDBC), an administrator can easily start and stop services, set up users, and views, and define alerts and notifications.
Enterprise security
Robust role-based access control (RBAC), row-based dynamic filtering, column-based dynamic masking with Apache Ranger integration provides centralized security administration and auditing for data lakes. Advanced row and column security empowers self-service data access.
Available on IBM Power Systems
Build on IBM Power Systems and drive the ability to crush the most advanced data applications — from the mission-critical workloads you run today to the next generation of AI.
Use cases
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Better data-driven decisions
Problem
New forms of unstructured and semi-structured data needing integration with traditional structured data.
Solution
Integrate new forms of semi and unstructured data (social media, sentiment, streaming audio/video, log and more) with your traditional structured data using advanced querying capabilities.
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Data warehouse modernization to free up bandwidth and storage
Problem
Massive amounts of historical or "cold" data taking up space and driving up costs in your enterprise data warehouse (EDW) built on Netezza, Oracle ExaData and Teradata.
Solution
Modernize your data warehouse to free up bandwidth and storage. Cloudera Enterprise Data Hub and Db2 Big SQL provide a superior platform for offloading historical or “cold” data in Oracle data marts and warehouses to Hadoop and also to port applications easily and accelerate time to value.
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Real-time and ad hoc data queries
Problem
Access to data in Hadoop is difficult for data users; data scientists, line of business analysts and developers.
Solution
Equip your data users with the right tools including Db2 Big SQL integrated with Apache Spark so they can do ad hoc and real-time queries to meet the needs of the business.
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Operational and process improvements
Problem
Growing requirements for operational and process improvements.
Solution
Use virtualization and federation to unify data access across the logical enterprise data warehouse, Cloud and Hadoop for more accurate data-driven decisions.
