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Natural Language SQL vs Savvina AI

Natural Language SQL

github.com

Savvina AI

savvina.ai

Side by side

FigureNatural Language SQLSavvina AI
Price fromFree€39/mo
Free planYesYes
Free trial——
Open source——
WebYesYes
macOSYes—
LinuxYes—
APIYesYes
Self-hostedYesYes
Plans published15
Spec score · AI SQL Generators8.4 (#3)8.0 (#6)
DeploymentThe recommended Docker setup requires Docker 20.10 or later with Compose v2 and about 10 GB of free disk space.All plans run on the customer’s own infrastructure via Docker, and the pricing page says Savvina does not touch customer data.
PurposeThe engine turns plain-English database questions into SQL, validates and executes the query, and streams back results.Savvina AI turns plain-English questions into SQL and returns database results within the customer’s own environment.

Plans

Natural Language SQL

  • Natural Language SQL EngineFree

Natural Language SQL pricing →

Savvina AI

  • CommunityFree
  • Starter€39 a month
  • Team€249 a month
  • Business€1,299 a month
  • EnterprisePriced on request

Savvina AI pricing →

In their own words

Natural Language SQL

Natural Language SQL turns plain-English questions about databases into SQL, validates and runs the query, then streams back results. It connects to PostgreSQL and MySQL, including multiple databases of the same type in parallel. Hybrid retrieval combines BM25 and sentence-transformer vectors to select schema context for a question. Users can review and edit generated SQL before execution, while the interface shows progress through query stages. Results can be sorted, paginated at 50 rows per page, downloaded as CSV or JSON, or copied as tab-separated text. SELECT queries receive a default limit, explicit result counts are capped at 1,000 rows, and execution times out after 30 seconds by default. INSERT, UPDATE and DELETE are allowed by default, with warning banners; the project recommends a read-only database user to block writes. Ollama runs locally by default, keeping questions, schema and generated SQL on the user’s machine. OpenAI, Gemini and Groq are optional cloud providers and receive the question, relevant schema portion and SQL context. The project is free under GPL-3.0. Its recommended Docker setup needs Docker 20.10 or later with Compose v2 and about 10 GB of free disk space.

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Savvina AI

Savvina AI turns plain-English questions into SQL and returns database results within the customer’s own environment. It supports follow-up queries, validates SQL as read-only, and adds LIMIT clauses automatically. Results can appear in eight chart types, from bar and line charts to gauges and numeric displays. The product lists 22 data sources, including PostgreSQL, BigQuery, Snowflake, MongoDB, Amazon S3, and Google Cloud Storage. Customers bring their own LLM provider; listed choices include Anthropic, OpenAI, Google, Ollama, OpenRouter, and vLLM. Plans run on customer infrastructure through Docker. Savvina says the LLM receives schema details rather than query results; users can exclude schemas, tables, or columns from prompts, and sensitive values are masked in results. Database passwords and API keys are encrypted at rest. The free Community plan is limited to one user and PostgreSQL and MySQL. Paid plans start at €39/mo, with no free trial. Enterprise pricing is custom and includes multiple deployments and air-gapped licenses.

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