A DBeaver alternative for database work done with coding agents.
DBeaver is the broader, free, open-source client for manual SQL across many engines. Valv is built for a different workflow. Your coding agent discovers the permitted schema, runs read-only queries, shows its work, and can turn the answer into a dashboard or file in the workspace.
Not a feature-for-feature clone. A better fit when the agent writes the query.
Pick the client that matches how you work.
There is no honest universal winner here. The decision turns on who writes the query and what should happen after the result comes back.
Choose DBeaver if you drive the database by hand.
DBeaver has the broader engine list and the deeper manual client, and the Community edition is free and open source. It covers a mature data editor, ER diagrams, data transfer and import-export, a SQL editor with autocomplete, and visual query building.
- You connect to database engines that Valv does not support.
- You design structures, move data between databases, and edit rows often.
- Your query editor is the center of the job.
Check the official DBeaver site.
Choose Valv if the agent writes the query.
Valv puts the coding agent inside the database workspace. The agent gets read-only database tools, the app records its tool calls and query results, and useful outputs can become files that survive the chat.
- You ask questions in plain language more often than you start with SQL.
- You need table and column controls for agent access.
- You want dashboards, query files, exports, and shared context in one workspace.
Valv also has a table viewer and SQL editor. Agent work is the reason to switch.
The same question takes a different path.
DBeaver gives you deep tools to write and run the statement. Valv makes the agent's database work inspectable and reusable.
A manual DBeaver workflow
- 1
Open the connection and find the relevant schema.
- 2
Write SQL with autocomplete, or build the query visually.
- 3
Run the statement and inspect the grid result.
- 4
Edit rows, export, or transfer the data to another database.
An agent-led Valv workflow
- 1
Ask a question in the workspace chat.
- 2
The agent discovers only the tables and columns allowed for AI.
- 3
Valv validates and runs a structured, read-only query from your machine.
- 4
Inspect the tool call and result, then save a dashboard, SQL file, or export when useful.
Valv adds control around the agent, not another chat box.
The important difference appears when the model needs live data. Valv owns that boundary and shows what crossed it.
Read-only database tools
The agent can list resources, inspect the allowed schema, and send structured analytics queries. It cannot call database insert, update, delete, or raw SQL tools.
Table and column controls for AI
Active schemas start visible. Hide a whole table or individual fields before the agent discovers them. Your own table viewer and SQL editor keep their normal access.
AI access
Tool calls and results you can inspect
Valv renders tool calls where they happen in the conversation. A factual answer can link back to the structured query and result behind it instead of leaving you with an unexplained paragraph.
Source: cancellation totals
Files and context that outlive the answer
Save live HTML dashboards, SQL, and exports in the workspace folder. In a git-backed workspace, choose which files sync to the team. Confirmed context and verified queries become shared workspace memory.
Both keep the database connection on your device. Chat changes the data path.
DBeaver is a desktop client that connects to your databases from your machine and keeps credentials there. That is a genuine strength, not a gap Valv can claim as its own.
Valv also connects to the database from your machine and encrypts database secrets with the OS keychain. When you use its optional AI chat, the allowed schema, your prompt, and the query results needed for the answer are processed through your chosen agent provider. The database credentials are not.
Source: DBeaver.
What leaves the database client?
DBeaver database work
Queries run from your machine and credentials stay on the device. DBeaver AI, in the paid editions, sends what it needs to its AI provider when you use it.
Valv database work with optional chat
Valv runs the query locally. The chosen model provider processes the prompt, permitted schema, and returned data needed to answer. Hide fields before asking if they should not enter that context.
DBeaver is free and open source. The paid tiers differ.
DBeaver Community costs nothing. Compare its paid subscription against Valv's one-time commercial license, and note what each free tier covers.
DBeaver
Free Community edition
Community is free and open source across many engines. DBeaver PE (Pro and Enterprise) is a paid per-user subscription that adds NoSQL support, extra tooling, and DBeaver AI.
See current DBeaver pricingValv Desktop
$99 Pro seat during beta
One-time commercial license with unlimited devices per seat. Personal, non-commercial use is free with every feature included.
See Valv pricingDBeaver alternative questions, answered
Is Valv a drop-in replacement for DBeaver?
No. DBeaver is the stronger choice if you want a free, broad, open-source client and spend most of your time writing SQL, drawing ER diagrams, moving data between engines, and editing rows by hand. Valv is the better fit when a coding agent writes the queries and you want that work inside a database client with read-only agent tools, AI access controls, visible results, and workspace context.
Which databases do DBeaver and Valv support?
DBeaver supports far more. The free Community edition connects to Postgres, MySQL, MariaDB, SQLite, Oracle, SQL Server, and many other engines over JDBC, and the paid editions add NoSQL sources. Valv has stable integrations for PostgreSQL, MySQL and MariaDB, SQLite, and ClickHouse, with MongoDB marked experimental.
Can I still browse tables and write SQL in Valv?
Yes. Valv has a live table viewer with filters and guarded row edits, plus a SQL editor that runs your SQL directly against the database. DBeaver remains the more complete manual client, with its data editor, ER diagrams, and data transfer tools. Valv's difference is the agent workflow around those database views.
Can a Valv agent change my database?
No. Valv gives agents policy-filtered discovery and structured query tools. It does not expose database insert, update, delete, or raw SQL tools to the agent. Your own table edits and SQL editor stay separate and can write when you choose to run or save changes.
How is Valv's agent different from DBeaver AI?
DBeaver AI, in the paid editions, is an assistant that helps you write SQL and work faster inside DBeaver. In Valv the agent runs the query itself through read-only tools, and every tool call and result is inspectable in the conversation. You control which tables and columns the agent can reach before it discovers them.
What can the agent see in Valv?
The schemas active in the workspace start visible. You can hide a whole table or individual columns such as email and card number in AI access. Hidden fields stay out of agent discovery and queries, while you can still use them yourself in the table viewer and SQL editor.
How do DBeaver and Valv handle privacy?
Both connect to databases from the user's device and keep database credentials there. Valv runs database queries from your machine and stores secrets in the OS keychain. Its optional chat sends your prompt, the allowed schema, and the query results needed for the answer through the coding-agent account you chose. Valv does not send database credentials to that provider.
How does DBeaver pricing compare with Valv?
DBeaver Community is free and open source. DBeaver PE (Pro and Enterprise) is a paid per-user subscription that adds NoSQL support, extra tooling, and DBeaver AI. Valv includes every feature free for personal, non-commercial use. During the beta, commercial Pro is a one-time $99 per seat with unlimited devices for that seat.
Try the agent-first DBeaver alternative.
Free for personal use, every feature included. Commercial use needs a seat at beta pricing. See pricing.