IBM StreamSets + SingleStore:
Faster Together
The world's most critical applications have real-time analytics at their core. To build these applications, your users demand an operational data platform that is:
- Connected to all the world's data
- Built with the most complex analytics in mind
- Designed for unlimited scale
The traditional approach
Most enterprises today suffer from database spaghetti — starting with an open-source database, adding a database for unstructured (JSON) data, then a cache, search database and data warehouse. This leads to latency, inaccuracy and costs from moving data and slow insights.
Intelligent applications require connectivity of data from the source systems, but also from this bowl of database spaghetti into an operational data platform to serve mission-critical needs.
Immediate data availability
Ingest millions of records per second
Data ready for analytics within milliseconds
Scale out to any demand
Fast analytics + hybrid search
Store structured, semi-structured and unstructured data
Run petabyte-scale analytical queries
Efficient relational, keyword-based search, vector search and graph-based query
Multi-model
Enterprise data integration
Stream real-time events (Kafka, Flink, etc.)
Native integration with lakehouse (Iceberg, etc.)
Enterprise-level security + consistency (ACID, etc.)
Unlimited connectivity
Leveraging StreamSets, get data from anywhere including applications, databases and even data warehouses.
Unparalleled analytical speeds
SingleStore's universal storage enables transactional, analytical and search queries at millisecond speeds for real-time apps
Iceberg ecosystem
Store data in watsonx.data using Iceberg format and natively query from SingleStore, the fast layer
