Keywords AI
Compare SingleStore and TigerGraph side by side. Both are tools in the Vector Databases category.
| Category | Vector Databases | Vector Databases |
| Website | singlestore.com | tigergraph.com |
Key criteria to evaluate when comparing Vector Databases solutions:
SingleStore is a distributed SQL database with built-in vector search capabilities.
TigerGraph is a scalable graph database platform for advanced analytics and AI.
Purpose-built databases for storing, indexing, and querying high-dimensional vector embeddings used in semantic search, RAG, and recommendation systems.
Browse all Vector Databases tools →A vector database stores high-dimensional numerical representations (embeddings) of data like text, images, or audio, and enables fast similarity search across millions or billions of vectors using approximate nearest neighbor algorithms.
For small to medium datasets (under 10 million vectors), pgvector in PostgreSQL works well and avoids adding another service. For larger datasets or when you need advanced features like hybrid search and real-time indexing, a dedicated vector database is recommended.
Match the embedding model to your use case. For general text search, models like OpenAI text-embedding-3 or Cohere embed-v3 work well. For domain-specific applications, consider fine-tuned models. Always benchmark with your actual data.