Comparison
qdrant vs vespa
Verdict
Pick qdrant if high-performance vector database with support for distributed deployment; pick vespa if vespa: A Java-based, scalable AI search platform for real-time vector and general data retrieval.
Markdown twin · qdrant alternatives · vespa alternatives
GraphCanon updated 3d
Trust & integrity
| Signal | qdrant | vespa |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- qdrant
- High-performance, massive-scale Vector Database and Vector Search Engine
- vespa
- The AI search platform
Stars
- qdrant
- 34k
- vespa
- 7.1k
Forks
- qdrant
- 2.5k
- vespa
- 732
Open issues
- qdrant
- 652
- vespa
- 250
Language
- qdrant
- Rust
- vespa
- Java
Adopt for
- qdrant
- High-performance vector database with support for distributed deployment.
- vespa
- Vespa: A Java-based, scalable AI search platform for real-time vector and general data retrieval.
Persona
- qdrant
- -
- vespa
- -
Runtime
- qdrant
- -
- vespa
- -
License
- qdrant
- Qdrant is available under the Apache License 2.0.
- vespa
- Apache-2.0
Last pushed
- qdrant
- Jul 28, 2026
- vespa
- Aug 18, 2026
Categories
- qdrant
- Data & Retrieval, Vector Databases
- vespa
- Data & Retrieval, Vector Databases
Trust and health
Open issues (now)
- qdrant
- 652
- vespa
- 250
Stars delta
- qdrant
- Unknown
- vespa
- +34 (30d)
Open issues delta
- qdrant
- Unknown
- vespa
- +7 (30d)
Full report
- qdrant
- Trust report
- vespa
- Trust report
Typed relationship
qdrant alternative vespaVespa and Qdrant both offer solutions for vector similarity search, providing a scalable and performant way to handle large datasets with high-dimensional vectors.
Choose qdrant if…
- qdrant is primarily Rust; vespa is Java.
- Qdrant supports self-hosted deployment along with a cloud option at https://cloud.qdrant.io/.
- Requirements: - Distributed deployment with sharding and replication is supported.; - No specific minimum RAM requirement provided. Performance and resource use will depend on the scale of embedding collections..
- Vespa and Qdrant both offer solutions for vector similarity search, providing a scalable and performant way to handle large datasets with high-dimensional vectors.
- Tags unique to qdrant: ai-search, embeddings-similarity, hnsw, knn-algorithm.
- qdrant ships Docker support for self-hosted deployment.
- - When scalability and performance are paramount in handling large-scale embeddings.
When NOT to use qdrant
- - Avoid if your project requires more traditional relational database features as Qdrant focuses exclusively on vectors.
- - If minimalistic setup is crucial, since Qdrant's capability for distributed deployment may introduce complexity that is not necessary for smaller-scale applications.
- - For use cases where non-Rust environments significantly limit the feasibility of integrating external tools.
Choose vespa if…
- vespa is primarily Java; qdrant is Rust.
- Vespa and Qdrant both offer solutions for vector similarity search, providing a scalable and performant way to handle large datasets with high-dimensional vectors.
- Tags unique to vespa: ai, big-data, java, machine-learning.
- Real-time indexing is critical
When NOT to use vespa
- Prefer solutions with lower setup complexity
- Team lacks Java expertise or prefers alternative languages
- Require no real-time capabilities and can rely on batch processing
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (qdrant/qdrant) · observed Jul 28, 2026
- GitHub forks (qdrant/qdrant) · observed Jul 28, 2026
- Last push (qdrant/qdrant) · observed Jul 28, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (vespa-engine/vespa) · observed Aug 18, 2026
- GitHub forks (vespa-engine/vespa) · observed Aug 18, 2026
- Last push (vespa-engine/vespa) · observed Aug 18, 2026
- License file (Apache-2.0) · observed Aug 18, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: qdrant 34k · vespa 7.1k (synced Jul 28, 2026).
Common questions
- What is the difference between qdrant and vespa?
- qdrant: High-performance, massive-scale Vector Database and Vector Search Engine. vespa: The AI search platform. See the comparison table for live GitHub stats and shared categories.
- When should I choose qdrant over vespa?
- Choose qdrant over vespa when qdrant is primarily Rust; vespa is Java; Qdrant supports self-hosted deployment along with a cloud option at https://cloud.qdrant.io/; Requirements: - Distributed deployment with sharding and replication is supported.; - No specific minimum RAM requirement provided. Performance and resource use will depend on the scale of embedding collections.; Vespa and Qdrant both offer solutions for vector similarity search, providing a scalable and performant way to handle large datasets with high-dimensional vectors; Tags unique to qdrant: ai-search, embeddings-similarity, hnsw, knn-algorithm; qdrant ships Docker support for self-hosted deployment; - When scalability and performance are paramount in handling large-scale embeddings.
- When should I choose vespa over qdrant?
- Choose vespa over qdrant when vespa is primarily Java; qdrant is Rust; Vespa and Qdrant both offer solutions for vector similarity search, providing a scalable and performant way to handle large datasets with high-dimensional vectors; Tags unique to vespa: ai, big-data, java, machine-learning; Real-time indexing is critical.
- When should I avoid qdrant?
- - Avoid if your project requires more traditional relational database features as Qdrant focuses exclusively on vectors. - If minimalistic setup is crucial, since Qdrant's capability for distributed deployment may introduce complexity that is not necessary for smaller-scale applications. - For use cases where non-Rust environments significantly limit the feasibility of integrating external tools.
- When should I avoid vespa?
- Prefer solutions with lower setup complexity Team lacks Java expertise or prefers alternative languages Require no real-time capabilities and can rely on batch processing
- Is qdrant or vespa more popular on GitHub?
- qdrant has more GitHub stars (33,629 vs 7,054). Stars measure visibility, not whether either tool fits your constraints.
- Are qdrant and vespa open source?
- Yes - both are open-source projects on GitHub (qdrant: Apache-2.0, vespa: Apache-2.0).
- Where can I find alternatives to qdrant or vespa?
- GraphCanon lists graph-backed alternatives at qdrant alternatives and vespa alternatives (qdrant markdown twin, vespa markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, qdrant or vespa?
- qdrant: Very active. vespa: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for qdrant and vespa?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: qdrant trust report; vespa trust report.