Comparison
natasha vs txtai
Verdict
Pick natasha if natasha is a Russian NLP toolkit offering capabilities such as embeddings, morphology analysis, named entity recognition (NER), syntax parsing, and sentence segmentation; pick txtai if txtai is an all-in-one AI framework that supports semantic search, LLM orchestration, and language model workflows, making it suitable for projects that require comprehensive AI capabilities in Python.
Markdown twin · natasha alternatives · txtai alternatives
GraphCanon updated Sep 20, 2026
5views this month
Trust & integrity
| Signal | natasha | txtai |
|---|---|---|
| Maintenance | Slowing (159d since push) As of Sep 20, 2026 · github_public_v1 | Very active (2d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 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
- natasha
- Solves basic Russian NLP tasks via API for lower level Natasha projects
- txtai
- All-in-one AI framework for semantic search, LLM orchestration and language model workflows
Stars
- natasha
- 1.3k
- txtai
- 13k
Forks
- natasha
- 120
- txtai
- 891
Open issues
- natasha
- 36
- txtai
- 10
Language
- natasha
- Python
- txtai
- Python
Adopt for
- natasha
- Natasha is a Russian NLP toolkit offering capabilities such as embeddings, morphology analysis, named entity recognition (NER), syntax parsing, and sentence segmentation.
- txtai
- txtai is an all-in-one AI framework that supports semantic search, LLM orchestration, and language model workflows, making it suitable for projects that require comprehensive AI capabilities in Python.
Persona
- natasha
- -
- txtai
- -
Runtime
- natasha
- -
- txtai
- -
License
- natasha
- MIT
- txtai
- Apache-2.0
Last pushed
- natasha
- Apr 13, 2026
- txtai
- Sep 15, 2026
Categories
- natasha
- Data & Retrieval, Model Training
- txtai
- AI Agents, Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training, Vector Databases
Trust and health
Maintenance
- natasha
- Slowing (36%)
- txtai
- Very active (96%)
Days since push
- natasha
- 159d
- txtai
- 2d
Open issues (now)
- natasha
- 36
- txtai
- 10
Stars delta
- natasha
- +5 (30d)
- txtai
- +69 (30d)
Open issues delta
- natasha
- +1 (30d)
- txtai
- 0 (30d)
Full report
- natasha
- Trust report
- txtai
- Trust report
Shared compatibility
- Python · natasha: Python runtime · txtai: Python runtime
Choose natasha if…
- License: natasha is MIT, txtai is Apache-2.0.
- Tags unique to natasha: morphology, ner, nlp, russian.
- For projects requiring deep processing of Russian language text data.
When NOT to use natasha
- If your project involves languages other than Russian as Natasha is specialized for the Russian language.
- In scenarios where advanced, fine-tuned models are required that go beyond basic NLP tasks, as Natasha focuses on foundational NLP capabilities.
Choose txtai if…
- License: txtai is Apache-2.0, natasha is MIT.
- Tags unique to txtai: agents, ai, ai-agents, information retrieval.
- Also covers AI Agents, Evaluation & Observability, Inference & Serving, Vector Databases.
- When you need a comprehensive framework that integrates semantic search, LLM orchestration, and language model workflows in a single package.
When NOT to use txtai
- If your project strictly requires a framework that is not Python-based, as txtai is specifically designed for Python environments.
- When you need a tool that focuses solely on a specific aspect of AI, such as only semantic search or only LLM orchestration, as txtai's all-in-one approach might introduce unnecessary complexity.
- If your project cannot accommodate the Apache-2.0 license, as txtai is distributed under this license and may not be suitable for projects with different licensing requirements.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (natasha/natasha) · observed Sep 20, 2026
- GitHub forks (natasha/natasha) · observed Sep 20, 2026
- Last push (natasha/natasha) · observed Apr 13, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (neuml/txtai) · observed Sep 20, 2026
- GitHub forks (neuml/txtai) · observed Sep 20, 2026
- Last push (neuml/txtai) · observed Sep 15, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: natasha 1.3k · txtai 13k (synced Sep 20, 2026).
Common questions
- What is the difference between natasha and txtai?
- natasha: Solves basic Russian NLP tasks via API for lower level Natasha projects. txtai: All-in-one AI framework for semantic search, LLM orchestration and language model workflows. See the comparison table for live GitHub stats and shared categories.
- When should I choose natasha over txtai?
- Choose natasha over txtai when License: natasha is MIT, txtai is Apache-2.0; Tags unique to natasha: morphology, ner, nlp, russian; For projects requiring deep processing of Russian language text data.
- When should I choose txtai over natasha?
- Choose txtai over natasha when License: txtai is Apache-2.0, natasha is MIT; Tags unique to txtai: agents, ai, ai-agents, information retrieval; Also covers AI Agents, Evaluation & Observability, Inference & Serving, Vector Databases; When you need a comprehensive framework that integrates semantic search, LLM orchestration, and language model workflows in a single package.
- When should I avoid natasha?
- If your project involves languages other than Russian as Natasha is specialized for the Russian language. In scenarios where advanced, fine-tuned models are required that go beyond basic NLP tasks, as Natasha focuses on foundational NLP capabilities.
- When should I avoid txtai?
- If your project strictly requires a framework that is not Python-based, as txtai is specifically designed for Python environments. When you need a tool that focuses solely on a specific aspect of AI, such as only semantic search or only LLM orchestration, as txtai's all-in-one approach might introduce unnecessary complexity. If your project cannot accommodate the Apache-2.0 license, as txtai is distributed under this license and may not be suitable for projects with different licensing requirements.
- Is natasha or txtai more popular on GitHub?
- txtai has more GitHub stars (12,959 vs 1,349). Stars measure visibility, not whether either tool fits your constraints.
- Are natasha and txtai open source?
- Yes - both are open-source projects on GitHub (natasha: MIT, txtai: Apache-2.0).
- Where can I find alternatives to natasha or txtai?
- GraphCanon lists graph-backed alternatives at natasha alternatives and txtai alternatives (natasha markdown twin, txtai 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, natasha or txtai?
- natasha: Slowing. txtai: 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 natasha and txtai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: natasha trust report; txtai trust report.