Vespa
Open-source big data serving engine with built-in vector search and ML inference.
About
Vespa is a serving engine for computing over large datasets at request time, combining full-text search, approximate vector search, structured filtering, and machine-learned model inference in one horizontally scalable system. Rather than gluing a vector database to a separate ranking service, applications express retrieval and ranking together: Vespa selects candidate data, evaluates tensors and ML models over it, and returns organized results typically within 100 milliseconds, all while absorbing continuous real-time writes. The engine is written in C++ and Java, originated at Yahoo where it serves hundreds of thousands of queries per second, and is used by large services for search, recommendation, RAG, and personalization at billion-document scale. It is open source under Apache 2.0 with frequent releases from master, deployable self-hosted or on the managed Vespa Cloud. Teams building serious search or recommendation infrastructure choose it when they outgrow single-purpose vector stores and need ranking logic to run next to the data.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- Vector Databases & Embeddings
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Advanced (4/5)
- License
- Apache-2.0
- Added
- Apr 3, 2026
Related Tools
Fast embedding inference server supporting many embedding models.
Open-source vector similarity search extension for PostgreSQL.
All-in-one embeddings database for semantic search, LLM orchestration, and language model workflows.
Library for representing and sending multimodal data by Jina AI.
Python client library for Qdrant vector database.
Efficient similarity search library by Meta for dense vector clustering and retrieval.