Comparison
deeplake vs postgresml
Verdict
Pick deeplake if deeplake is an AI Data Runtime for Agents that integrates a serverless PostgreSQL with a multimodal data lake, designed for scalable retrieval and training; pick postgresml if postgresML offers PostgreSQL with GPU acceleration for ML, distinguishing by its support of embedding operations directly into SQL queries.
Markdown twin · deeplake alternatives · postgresml alternatives
GraphCanon updated Sep 30, 2026
14views this month
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Trust & integrity
| Signal | deeplake | postgresml |
|---|---|---|
| Maintenance | Slowing (119d since push) As of Sep 18, 2026 · github_public_v1 | Dormant (412d since push) As of Aug 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Aug 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · 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
- deeplake
- AI Data Runtime for Agents
- postgresml
- Postgres with GPUs for ML/AI apps
Stars
- deeplake
- 9.2k
- postgresml
- 6.8k
Forks
- deeplake
- 722
- postgresml
- 365
Open issues
- deeplake
- 67
- postgresml
- 149
Language
- deeplake
- C++
- postgresml
- Rust
Adopt for
- deeplake
- Deeplake is an AI Data Runtime for Agents that integrates a serverless PostgreSQL with a multimodal data lake, designed for scalable retrieval and training.
- postgresml
- PostgresML offers PostgreSQL with GPU acceleration for ML, distinguishing by its support of embedding operations directly into SQL queries.
Persona
- deeplake
- -
- postgresml
- -
Runtime
- deeplake
- -
- postgresml
- -
License
- deeplake
- Deeplake is available under the Apache-2.0 license, allowing for free use, modification, and distribution.
- postgresml
- MIT
Last pushed
- deeplake
- May 21, 2026
- postgresml
- Jul 1, 2025
Categories
- deeplake
- Data & Retrieval, Model Training, Vector Databases
- postgresml
- Data & Retrieval, Model Training, Vector Databases
Trust and health
Maintenance
- deeplake
- Slowing (36%)
- postgresml
- Dormant (18%)
Days since push
- deeplake
- 119d
- postgresml
- 412d
Open issues (now)
- deeplake
- 67
- postgresml
- 149
Stars delta
- deeplake
- +15 (30d)
- postgresml
- +3 (30d)
Open issues delta
- deeplake
- +4 (30d)
- postgresml
- 0 (30d)
Full report
- deeplake
- Trust report
- postgresml
- Trust report
Choose deeplake if…
- deeplake is primarily C++; postgresml is Rust.
- License: deeplake is Apache-2.0, postgresml is MIT.
- Pricing: Deeplake offers a free tier with options for premium services, though specific pricing details are not provided in the repository..
- Requirements: Min 4 GB RAM; Installation can be done via pip, making it accessible for Python environments..
- Tags unique to deeplake: agent, agentic-rag, clawbot, computer-vision.
- When you need a serverless PostgreSQL setup integrated with a multimodal data lake for efficient data retrieval and training.
When NOT to use deeplake
- If your project does not require serverless PostgreSQL or multimodal data handling capabilities.
- When you are looking for a solution that does not support C++ as the primary language, as Deeplake is built with C++.
- If your use case does not benefit from the specific integration of PostgreSQL with a data lake, and you prefer a more traditional database setup.
Choose postgresml if…
- postgresml is primarily Rust; deeplake is C++.
- License: postgresml is MIT, deeplake is Apache-2.0.
- Tags unique to postgresml: ann, approximate-nearest-neighbor-search, classification, clustering.
- Requires integration of machine learning tasks directly within PostgreSQL queries
When NOT to use postgresml
- Teams not utilizing or unwilling to migrate to PostgreSQL databases
- Applications where GPU access is limited, thus constraining ML capabilities
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (activeloopai/deeplake) · observed Sep 20, 2026
- GitHub forks (activeloopai/deeplake) · observed Sep 20, 2026
- Last push (activeloopai/deeplake) · observed May 21, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 30, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (postgresml/postgresml) · observed Sep 20, 2026
- GitHub forks (postgresml/postgresml) · observed Sep 20, 2026
- Last push (postgresml/postgresml) · observed Jul 1, 2025
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deeplake 9.2k · postgresml 6.8k (synced Sep 20, 2026).
Common questions
- What is the difference between deeplake and postgresml?
- deeplake: AI Data Runtime for Agents. postgresml: Postgres with GPUs for ML/AI apps. See the comparison table for live GitHub stats and shared categories.
- When should I choose deeplake over postgresml?
- Choose deeplake over postgresml when deeplake is primarily C++; postgresml is Rust; License: deeplake is Apache-2.0, postgresml is MIT; Pricing: Deeplake offers a free tier with options for premium services, though specific pricing details are not provided in the repository.; Requirements: Min 4 GB RAM; Installation can be done via pip, making it accessible for Python environments.; Tags unique to deeplake: agent, agentic-rag, clawbot, computer-vision; When you need a serverless PostgreSQL setup integrated with a multimodal data lake for efficient data retrieval and training.
- When should I choose postgresml over deeplake?
- Choose postgresml over deeplake when postgresml is primarily Rust; deeplake is C++; License: postgresml is MIT, deeplake is Apache-2.0; Tags unique to postgresml: ann, approximate-nearest-neighbor-search, classification, clustering; Requires integration of machine learning tasks directly within PostgreSQL queries.
- When should I avoid deeplake?
- If your project does not require serverless PostgreSQL or multimodal data handling capabilities. When you are looking for a solution that does not support C++ as the primary language, as Deeplake is built with C++. If your use case does not benefit from the specific integration of PostgreSQL with a data lake, and you prefer a more traditional database setup.
- When should I avoid postgresml?
- Teams not utilizing or unwilling to migrate to PostgreSQL databases Applications where GPU access is limited, thus constraining ML capabilities
- Is deeplake or postgresml more popular on GitHub?
- deeplake has more GitHub stars (9,239 vs 6,817). Stars measure visibility, not whether either tool fits your constraints.
- Are deeplake and postgresml open source?
- Yes - both are open-source projects on GitHub (deeplake: Apache-2.0, postgresml: MIT).
- Where can I find alternatives to deeplake or postgresml?
- GraphCanon lists graph-backed alternatives at deeplake alternatives and postgresml alternatives (deeplake markdown twin, postgresml 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, deeplake or postgresml?
- deeplake: Slowing. postgresml: Dormant. 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 deeplake and postgresml?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deeplake trust report; postgresml trust report.