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SingleStore is enhancing its database platform with a new release that expands functionality for generative AI workloads, as well as both transactional and analytical data workloads.
The new SingleStore Pro Max database, part of the SingleStore 8.5 update, includes new indexed vector search capabilities to help organizations support generative AI applications and retrieval augmented generation (RAG) use cases.
Although the SingleStore database has incorporated vector capabilities since 2017—when the company was known as MemSQL—this new update offers more advanced features. SingleStore rebranded in 2020, integrating both Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP) into one unified platform.
As the demand for generative AI workloads has grown, so has the need for vector database capabilities. Native database platforms like Pinecone and other vendors such as DataStax, Neo4j, MongoDB, PostgreSQL, and Oracle have recently added vector support. According to SingleStore’s CEO, combining existing database capabilities with vectors is crucial, rather than focusing solely on a vector-specific database which only adds complexity to the AI stack.
With the Pro Max release, SingleStore enhances support for vector search across both structured and unstructured data. From 2017, SingleStore supported vector search, but the new release includes improved algorithms like product quantization (PQ), Hierarchical Navigable Small World (HNSW), and Approximate Nearest Neighbor (ANN) for faster and more accurate indexing.
The new index vector search capabilities mean organizations can better utilize their data for both search and support gen AI applications. SingleStore’s CEO stated that while vector-only databases might quickly enable entry into the gen AI space, they fail to address the broader data landscape most organizations need.
“To fully benefit from a generative AI data estate, simplicity and data consolidation are essential,” Verma emphasized.
Additionally, the SingleStore Pro Max release bolsters Change Data Capture (CDC) capabilities to integrate data from MySQL, MongoDB, and Apache Iceberg-based data lakes into a single database. Apache Iceberg, an open-source data lake table format, is used by vendors like IBM and Snowflake. According to Verma, this feature strengthens SingleStore’s partnerships with IBM and Snowflake, facilitating easier integration.
“CDC capability lets our customers bring data from various sources into SingleStore, which is crucial for the entire retrieval and augmented generation workflow,” Verma remarked.