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Vespa project preview

Vespa

The open big data serving engine for vector search, lexical search, and machine learning scoring.

LicenseApache-2.0
GitHub stars5.8k
Last commit1 weeks ago
Tags6 topics
Hybrid SearchAiMachine LearningBig DataSearch EngineVector Search
Overview

Why consider Vespa?

Vespa is an open-source big data engine developed by Yahoo for real-time vector search, lexical search, and ML model inference over billions of documents with sub-100ms latencies.

Guided learning

Learn Vespa by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 3 sections
In this guide3 sections

Overview of Vespa

Vespa scales real-time search, ranking, and machine learned model inference across massive document corpora. It performs hybrid search (combining sparse BM25 text match with dense HNSW vector search) and re-ranks results with ONNX machine learning models in real-time.

Starting Vespa with Docker

bash
1docker run -d \
2 --name vespa \
3 -p 8080:8080 -p 19071:19071 \
4 vespaengine/vespa:latest

Deploying an Application Package

bash
1vespa deploy --wait 300 path/to/application_package

Query with vector embeddings and text filters using the REST endpoint:

bash
1curl -X POST http://localhost:8080/search/ \
2 -H "Content-Type: application/json" \
3 -d '{"yql": "select * from sources * where userInput(@query);", "query": "autonomous AI agents"}'

Vespa is licensed under the Apache License Version 2.0.

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Vespa FAQs

Vespa is listed as a Ai Machine Learning tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository and official website for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

Vespa is listed under the Apache-2.0 license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

Vespa is listed as an alternative to Weaviate. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.