SayQL vs DBeaver
Updated
DBeaver is a mature, universal database tool with AI features, in a free Community edition and paid editions. SayQL is narrower: a desktop SQL client built around what AI may see and do on your databases.
Choose DBeaver for the widest database support and admin tooling. Choose SayQL when AI and agents touch production data and you want counts instead of rows, columns that never reach the AI, and a record of every query.
Checked on 3 November 2026 against each product's own docs, code and pricing; every cell links to its source. Spotted something out of date? Email hello@azenvoc.com and we'll fix it.
Side by side
| SayQL | DBeaver | |
|---|---|---|
| What it is | Desktop SQL client (macOS, Windows, Linux) with AI, plus an optional self-hosted team server source | Universal database tool (SQL editor, data editor, admin tools) with AI features; free Community edition and paid editions, plus a web version (CloudBeaver) source |
| Status | Maintained; 0.6.0 released 2026-11-03 source | Maintained; Community 26.2.4 released early November 2026 source |
| Licence | App: open source, Apache 2.0. Team server: paid licence source | Community: open source, Apache 2.0. Lite, Enterprise, Ultimate, Team, CloudBeaver Enterprise: commercial source |
| Price | App free. Team server $149 a month for up to 10 people, 30-day trial source | Community free. Paid desktop from $113 a year (Lite) to $510 a year (Ultimate); Team $1,630 a year source |
| Databases | PostgreSQL, MySQL, MariaDB, SQLite, SQL Server, Azure SQL source | More than 100, including NoSQL, cloud and analytics databases source |
| AI models | Claude, OpenAI, Gemini, OpenRouter, Mistral, Groq, DeepSeek, any OpenAI-compatible API; local models with Ollama or LM Studio source | Community: OpenAI and GitHub Copilot. Paid: also Azure OpenAI, Gemini, Claude, Bedrock, Grok, and local models through Ollama source |
| Plain English to SQL | Yes: SQL appears in the editor as you type, from your schema and approved notes source | Yes: an @ai command in the SQL editor, AI Chat and AI autocomplete source |
| Multi-step questions | Yes (beta): plans, runs read-only steps, checks its work, cites each query source | Not documented as a multi-step agent; AI Chat can run the SQL it writes, and paid editions add AI tools that drive DBeaver actions source |
| MCP server for AI agents | Yes: a local MCP server for Claude Code, Cursor and others, and an HTTP gateway on the team server source | Paid editions: a local MCP server documented from 26.3, switched on per connection; CloudBeaver Enterprise has one too. Not in Community source |
| What the AI sees of your data | Schema by default. Per connection you choose what AI sees of results: nothing, counts and summaries (default), masked rows, or all rows source | Table and column names by default, limited by a per-table scope. Sample rows optional (off by default, 10 to 200 rows). Whether chat results go to the AI is not documented source |
| Keep chosen columns from the AI | Yes: columns marked never send are refused in any form and withheld from results source | Not documented: the scope setting works per table, not per column source |
| Read-only for AI | Read-only by default: statements are checked before they run and run in a read-only transaction; AI apps can't change data source | No AI read-only mode: AI SELECTs run immediately, changes ask for confirmation by default, and each can be set to run without asking. A read-only connection option exists source |
| Record of AI queries | Yes: a local log of what each AI app ran; on the team server, one log of every query from people and agents, whose rows can't be edited source | No dedicated audit log; AI requests can be written to the debug log source |
| Per-agent or per-user rules | Block or allow each AI app. Team server: each agent its own key, databases, tables and rows source | Each AI tool set to Ask or Always allow (paid); MCP switched on per connection. Per-user AI rules not documented source |
| Where it runs, where data goes | Runs on your computer; the team server runs on your servers and your data never reaches us source | Desktop app; Team and CloudBeaver run on your servers. Metadata (and sample rows if on) goes to the chosen AI provider; Ollama keeps it local source |
| Interface | Desktop app source | Desktop app; web app (CloudBeaver) source |
| Learns about your database | Shared notes about the database that people approve and SayQL keeps true as the schema changes; no training on question–SQL pairs source | Not documented source |
What DBeaver does better
- Supports far more databases: over 100, including NoSQL, cloud and analytics engines. source
- ER diagrams you can edit, which generate SQL, across connections. source
- A full toolbox: data editor, tasks, maintenance tools, and data transfer and compare wizards. source
- A mature project with a large community (about 52,000 GitHub stars) and regular releases. source
- A web version (CloudBeaver) for teams that want a browser-based tool on their own server. source
How SayQL handles AI access
- Counts, not rows, by default. For each connection you choose what AI apps see of results: nothing, counts and summaries, masked rows or all rows. See what AI apps may see.
- Columns that never reach the AI. Mark a column never send and any query that could read it is refused, and it's withheld from results. See never-send columns.
- Read-only, enforced. Every statement is checked before it runs and runs in a read-only transaction; AI apps can't change data. See how queries run safely.
- A record of what AI ran. See every query each AI app ran, and block an app in one click. On the team server, one log covers every person and agent. See agent activity.
- Per-agent keys on your own server. The self-hosted team server gives each agent its own key, databases, tables and rows. See SayQL for teams.
Questions
Does DBeaver send query results to the AI?
Table and column names by default, limited by a per-table scope. Sample rows optional (off by default, 10 to 200 rows). Whether chat results go to the AI is not documented. source In SayQL: schema by default. Per connection you choose what AI sees of results: nothing, counts and summaries (default), masked rows, or all rows. source
Can DBeaver keep a column away from the AI?
Not documented: the scope setting works per table, not per column. source In SayQL, yes: columns marked never send are refused in any form and withheld from results. source
Is DBeaver read-only for AI?
No AI read-only mode: AI SELECTs run immediately, changes ask for confirmation by default, and each can be set to run without asking. A read-only connection option exists. source In SayQL: read-only by default: statements are checked before they run and run in a read-only transaction; AI apps can't change data. source
Does DBeaver have an MCP server for AI agents?
Paid editions: a local MCP server documented from 26.3, switched on per connection; CloudBeaver Enterprise has one too. Not in Community. source In SayQL, yes: a local MCP server for Claude Code, Cursor and others, and an HTTP gateway on the team server. source
Other comparisons
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- SayQL vs MCP Toolbox for Databases
- SayQL vs Vanna
- All tools side by side
Download SayQL: the app is free and open source.
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