Migrating Your Generative AI Apps From Rockset to SingleStore: A Guide for Engineers

If you've developed your generative AI infrastructure on Rockset and are on the hunt for an alternative, SingleStore provides a powerful option to keep your applications running. This guide walks you through migrating your generative AI applications, highlighting how SingleStore's features power your AI-driven solutions.

Why SingleStore for generative AI?

Advanced vector operations

SingleStore excels in vector operations crucial for generative AI:

• Indexed ANN (Approximate Nearest Neighbor) search
• k-Nearest Neighbor (kNN) search via dot product, Euclidean distance and cosine similarity

Scalable architecture for AI workloads

SingleStore's distributed architecture and separation of compute from storage ensures your generative AI apps can handle growing data volumes and increasing inference requests without performance degradation.

Comprehensive AI ecosystem integration

Seamless integration with leading AI platforms like OpenAI, AWS Bedrock and Hugging Face allows for easy development and deployment of sophisticated generative AI applications.

IVF and HNSW for efficient ANN search

SingleStore supports both Inverted File (IVF) and Hierarchical Navigable Small World (HNSW) indexing for efficient ANN searches. IVF partitions vectors into clusters, creating an inverted index from centroids to vectors, which allows searching only in relevant clusters during queries. HNSW builds a multi-layered graph where nodes represent vectors and edges connect close vectors, enabling efficient navigation through the graph to find nearest neighbors.

Both methods significantly reduce search time compared to kNN, with IVF's search time roughly proportional to the square root of the total number of vectors — while HNSW offers faster search speeds but requires more memory. SingleStore's support for these indexing mechanisms allows users to run vector searches across millions of vectors efficiently, making it suitable for large-scale generative AI applications.

Full-text search

Similar to Rockset, SingleStore offers robust full-text search capabilities integrated into its database engine. This feature is built on the open-source Lucene technology, which is a standard for full-text searching in the industry. Key features include:

• Inverted index. Efficiently keeps track of all words in a document and their frequency, enabling fast searches.
• Relevance scoring (via BM25). Determines the relevance of search results, allowing for sorting by relevance.
• Integration with SQL. Full-text search can be seamlessly integrated with SQL queries, enabling complex searches that combine structured and unstructured data.
• Distributed index. The full-text index is partitioned using the same sharding pattern as the table, allowing for efficient distributed searches.

Performance optimization

• Benchmark queries and inference requests to ensure peak performance
• Leverage ANN indexing for faster similarity searches
• Scale AI processing horizontally using SingleStore's distributed architecture
• Enhance context retrieval with hybrid search, improving response accuracy and reducing hallucinations
• Enable real-time insights by utilizing fast data ingestion for continuous updates
• Build multi-modal AI applications processing text, structured data and vector representations of images or audio
• Create intelligent, AI-driven analytics by combining SingleStore's analytical capabilities with generative AI models

Conclusion

Transitioning your intelligent, generative AI applications from Rockset to SingleStore opens up new possibilities for enhancing your AI capabilities. With its advanced vector operations, structured data support, scalable architecture, comprehensive AI ecosystem integration and support for cutting-edge indexing techniques like IVF and HNSW, SingleStore provides a robust foundation for the next generation of AI-driven applications.

As you embark on this AI-focused transition, our team at SingleStore is committed to supporting your journey. We offer expert support, extensive documentation on best practices and migration tools optimized for your AI workloads to ensure a smooth transition for your generative AI applications.

Book a call with one of our engineers to get step-by-step advice on how to migrate from Rockset, optimize your setup and tap into SingleStore's AI-friendly features. We'll help you navigate the transition and establish why we’re the only Rockset alternative you need for your intelligent, generative AI workloads.