Overview
Research summary
Vespa is an application-serving and search platform for selecting, ranking, and aggregating information from changing datasets. It supports vectors, text, tensors, and structured fields, and can apply machine-learned ranking or inference during query processing. Developers define schemas, ranking behavior, and application components for search, recommendation, personalization, or retrieval pipelines. The open-source repository contains the software needed for self-hosting, while Vespa Cloud is a separate managed offering. Its distributed serving design targets applications that need more control than vector similarity alone.
Repository summary
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services available
The provider offers paid products or services. Free options may also be available.
Commercial offering checked 2026-10-02.
Licence scope
Implementation
Recorded implementation details and interfaces for Vespa.
Implementation details
Java and C++ distributed search and ranking platform
- Languages
- Java
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- Unavailable
- Open issues
- Unavailable
- Last push
- Unavailable
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
Documentation
Recorded references and research provenance for this entry.
Recorded sources 6
- https://vespa.ai Project page
- https://github.com/vespa-engine/vespa Linked repository · Research reference
- https://github.com/vespa-engine/vespa/blob/master/README.md Research reference
- https://api.github.com/repos/vespa-engine/vespa Research reference
- https://vespa.ai/pricing/ Commercial offering evidence
- https://blog.vespa.ai/using-vespa-cloud-resource-suggestions-to-optimize-costs/ Commercial offering evidence
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06
Community & social 2 channels
Communities
- Slackslack.vespa.aiOfficial
- GitHub Discussionsgithub.com/vespa-engine/vespa/discussionsOfficial
Link details for GitHub Discussions
- Last checked