Redis Vector vs SingleStore: Vector Databases Comparison
Compare Redis Vector and SingleStore side by side. Both are tools in the Vector Databases category.
The short answer
Choose Redis Vector if multi-modal capabilities: vector search, caching, sessions, and messaging in one platform.
Choose SingleStore if unified platform combining transactional, analytical, and vector workloads.
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Quick Comparison
| Category | Vector Databases | Vector Databases |
| Website | redis.io | singlestore.com |
Pros & Cons: Redis Vector vs SingleStore
- +Multi-modal capabilities: vector search, caching, sessions, and messaging in one platform
- +Sub-millisecond latency with in-memory data storage
- +Multiple deployment options: fully managed cloud, self-managed, or open source
- +HNSW and Flat indexing support for flexible search requirements
- +Eliminates need for multiple tools, reducing architectural complexity
- −In-memory storage can be expensive at large scale
- −Not purpose-built solely for vector search like dedicated vector databases
- −May require additional configuration for optimal vector search performance
- −Pricing can become complex with usage-based model
- +Unified platform combining transactional, analytical, and vector workloads
- +Co-located vector data with relational data for powerful SQL queries
- +Multiple vector index types (FLAT, IVF_FLAT, IVF_PQ, HNSW_FLAT, HNSW_PQ)
- +MySQL and MongoDB wire protocol compatibility for easy integration
- +Proven at scale with 100+ Fortune 500 customers
- −More complex than dedicated vector databases for pure vector search use cases
- −Pricing not transparently published
- −May have higher learning curve for teams unfamiliar with distributed SQL
- −Recent acquisition may lead to product changes
How to Choose a Vector Databases Tool
Key criteria to evaluate when comparing Vector Databases solutions:
About Redis Vector
Redis offers vector search capabilities through Redis Cloud (fully managed), Redis Software (self-managed), and Redis Open Source, with the Redis Vector Library (RedisVL) simplifying working with vectors in Redis. Unlike dedicated vector databases, Redis offers multi-modal capabilities—handling vector search, real-time caching, feature storage, and pub/sub messaging in a single system, eliminating the need for multiple tools and reducing complexity and cost. Redis supports HNSW (Hierarchical Navigable Small World) for fast approximate nearest neighbor (ANN) search and Flat indexing for exact search. Vector search lives alongside caching, sessions, and messaging in one platform, with data staying in memory with no network hops between systems, enabling core operations to run at sub-millisecond latency. Founded in 2011 and headquartered in San Francisco (relocated from Mountain View in 2024), Redis serves enterprises across multiple industries with proven performance at scale.
About SingleStore
SingleStore is a real-time, unified, distributed SQL database that combines transactional, analytical, and vector data workloads in a single platform. MySQL and MongoDB wire protocol-compatible, SingleStore enables organizations to scale from one to one million customers, handling SQL, JSON, full text, and vector workloads all in one unified platform. Unlike traditional vector databases, SingleStore stores vector data in relational tables alongside other types of data, allowing easy querying of extended metadata and other attributes with the full power of SQL. The system supports both semantic search using FLAT, IVF_FLAT, IVF_PQ, IVF_PQFS, HNSW_FLAT, and HNSW_PQ vector indexes, with dot product and Euclidean distance for similarity matching. Founded in 2011 and headquartered in San Francisco, SingleStore serves hundreds of customers including 100+ Fortune 500, Forbes Global 2000, and Inc. 5000 brands. The company was acquired by Vector Capital in September 2025.
What is Vector Databases?
Purpose-built databases for storing, indexing, and querying high-dimensional vector embeddings used in semantic search, RAG, and recommendation systems.
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