Comparison

Database clients, compared on six things that matter

12 tools · Checked 2026-08-11

Engine breadth, cost and openness, platform reach, production safety, AI, and schema tooling. AddisDB does not win every row, and the rows it loses are marked as plainly as the ones it wins.

What the columns mean

Engine breadth — How many database engines and data-file formats it can actually open.
Cost & openness — What it costs to use for real work, and whether you can read the source.
Platform reach — Which operating systems and surfaces it runs on.
Production safety — What stands between you and the wrong statement on a production database.
AI capability — What the AI does, what it costs, and where your schema and keys go.
Schema tooling — Diagrams, diffs, and getting a schema change from your laptop to production.

AddisDB (ours)

A desktop client built around the idea that changing production should not be a leap of faith. Free for databases on your own machine.

Engine breadth — Strong: 95 engines and data-file formats, from Postgres and MySQL through Mongo, Redis, Cassandra and Neo4j to Snowflake, BigQuery, ClickHouse and local CSV/Parquet/GeoJSON. Every engine is on every plan, including the free one.
Cost & openness — Good: Free forever for databases on your own machine — the whole client, every engine, no account and no card. $49/year to reach databases that are not local; $99/user/year for teams; $299/user/year for SSO, audit log and RBAC. Source is not public.
Platform reach — Strong: macOS, Windows and Linux as a native app, plus a CLI with a TUI and a VS Code extension that share the same core.
Production safety — Strong: Connections can be marked read-only; statements are classified before they run, so an unqualified DELETE or a DROP is stopped rather than reported afterwards. A prod environment tag adds write guards, and row-count thresholds catch the statement that would hit more rows than you meant.
AI capability — Strong: Plain-English to SQL, schema-aware, with the generated statement shown for you to edit before it runs. Bring your own provider key: it is stored in the OS credential store, calls go straight to your provider, and AI is included on the free tier because we are not the ones paying for the tokens.
Schema tooling — Strong: ERD of tables and foreign keys, schema diff between databases, and a migration preview that shows the exact SQL plus the dangerous parts — dropped columns, rewrites, locks — before anything runs. Reads Drizzle Kit and Prisma changes too.

DBeaver

The most widely used open-source database client, and the broadest engine support of anything on this page.

Engine breadth — Strong: The widest support here — 80+ engines in the Community Edition, and anything with a JDBC driver on top of that. If you have an obscure database, this is the tool most likely to open it.
Cost & openness — Strong: Community Edition is free and Apache-2.0 — genuinely open source, commercial use included, no seat count. Paid tiers add features rather than engines: Lite around $113/user/year, Enterprise around $250/year, Ultimate around $500/year. Perpetual licences ended after 23.3.
Platform reach — Good: Windows, macOS and Linux. It is an Eclipse/Java application, so it is heavier to start and looks less native than the Rust and Electron clients here — a real daily-use difference, not a benchmark quibble.
Production safety — Limited: Connections can be marked read-only and production connections can be colour-coded, which helps you notice. There is no statement classification stopping a destructive write before it runs in the Community Edition.
AI capability — Limited: An AI assistant exists but is a PRO feature, so the free edition most people use has none.
Schema tooling — Good: ER diagrams in Community; schema compare and migration tooling are PRO. Mature and thorough where present.

JetBrains DataGrip

A database IDE. The best SQL editor of the group, priced and shaped like a developer tool rather than a database browser.

Engine breadth — Good: Deep, first-class support for the major engines — MySQL, Postgres, SQL Server, Oracle, MongoDB, Redis — plus 25+ more over JDBC. Fewer than DBeaver, but the support it has is more thorough.
Cost & openness — Limited: The most expensive here: $299/year for an individual, $979/user/year for an organization. A free non-commercial licence arrived in October 2025, which covers hobby use but not your job. AI is a further paid add-on. Not open source.
Platform reach — Good: Windows, macOS and Linux, on the JVM. Also available inside the other JetBrains IDEs if you already pay for one.
Production safety — Good: Read-only mode per data source and a confirmation step for statements that modify data, which is more deliberate than most. It warns rather than classifying and blocking.
AI capability — Good: AI Assistant does natural-language SQL and explanation, and it is good — but it is a separate subscription on top of the licence (about $100/year for an individual), so the price of the AI story is the licence plus the add-on.
Schema tooling — Strong: The strongest refactoring in the group: rename a column and it updates the references. Diagrams, schema compare and migration generation are all first-class.

TablePlus

The fastest, most native-feeling client here, sold once rather than rented. Deliberately minimal.

Engine breadth — Good: Around 20 of the engines people actually use — the major relational ones plus Redis, Mongo and a few cloud warehouses. Broad enough for most, narrow next to DBeaver.
Cost & openness — Good: The only genuinely perpetual licence in the table: $99 Basic, $129 Standard, $79/seat for teams of 3+. You keep the version you bought forever; a year of updates is included and renewal only buys newer releases. The free trial is limited to 2 tabs and 2 windows. Not open source.
Platform reach — Strong: macOS, Windows, Linux — and iOS, which nothing else here offers. The macOS build in particular is the most native-feeling app in this comparison.
Production safety — Good: A read-only mode and a safe-mode prompt before committing changes. Lightweight by design — it asks you to confirm rather than analysing what the statement would do.
AI capability — None: No meaningful built-in AI. That is a positioning choice rather than an oversight: the product is about being fast and out of the way.
Schema tooling — Limited: Competent schema editing and inline structure changes, but no ERD, no schema diff, and no migration review. Not what it is for.

QoreDB

The closest thing to AddisDB on this page: Rust and Tauri, local-first, SQL and NoSQL, with a diff-before-you-commit workflow — and open source.

Engine breadth — Good: 15 native drivers covering the Postgres family (including Supabase, Neon and TimescaleDB), MySQL/MariaDB, SQL Server, SQLite, DuckDB, MongoDB, Redis, CockroachDB, Elasticsearch, OpenSearch and ClickHouse. Native drivers rather than JDBC, so what it supports it supports properly.
Cost & openness — Strong: Free core and Apache-2.0 open source, with a Pro tier sold as a one-time purchase rather than a subscription. Between the licence and the pricing model this is one of the two best-value options here.
Platform reach — Good: macOS, Windows and Linux. Rust and Tauri, so it starts in about a second and stays small — the same architectural bet AddisDB made, with the same payoff.
Production safety — Good: Production safety guards, an encrypted credential vault using Argon2, SSH tunnelling and zero telemetry. The Sandbox is the standout: edit locally, see every insert, update and delete as a diff, and generate a migration script before anything reaches the database.
AI capability — Good: An AI assistant for query generation, explanation and error correction, bring-your-own-key — but it is a Pro feature, where AddisDB includes BYOK AI on the free tier.
Schema tooling — Good: Interactive ER diagram with isolate and focus, Sandbox-generated migration scripts with pre-conditions, and Time Travel with visual data diff for comparing row versions.

Beekeeper Studio

A clean, friendly, open-source client that does the everyday things well and does not try to be an IDE.

Engine breadth — Limited: The common ones — Postgres, MySQL, SQL Server, SQLite, and a handful more. The Community Edition covers "common databases"; the full set is a paid tier, so engine breadth is partly a pricing question here.
Cost & openness — Strong: Community Edition is free under an OSI-approved licence, with no tab limits and unlimited connections, intended for individuals and organizations under 10 employees or $1M revenue. Paid tiers run $9/month (Indie), $14/month (Professional) and $18/month (Business) billed yearly. Some newer code is source-available rather than open source.
Platform reach — Good: Windows, macOS and Linux. Electron, so heavier than the Rust clients but lighter than the Java ones.
Production safety — Limited: A read-only connection mode, which is the main guardrail. No statement classification or migration review.
AI capability — Limited: An AI Shell is available on paid tiers. Not present in the Community Edition most people run.
Schema tooling — Limited: Table structure editing and straightforward browsing. No ERD or schema diff — it is honest about being a SQL editor and table browser.

DbVisualizer

A long-established cross-platform client with strong diagramming, where most of what you want is behind the Pro edition.

Engine breadth — Good: 30+ engines over JDBC, including the enterprise ones — Oracle, Db2, SQL Server, Informix — that lighter clients skip.
Cost & openness — Limited: A free edition exists but omits a lot: table management, data editing, query builders, import/export and AI are all Pro. Pro is $199/user for the first year then $89/year to renew, or $229/$119 with premium support. Each subscription carries a perpetual licence for versions released during the term. Not open source.
Platform reach — Good: Windows, macOS, Linux and UNIX, including Arm64 and Apple Silicon builds. Java-based.
Production safety — Limited: Permissions and connection-level restrictions, and a clear separation between environments. No statement classification stopping a destructive write.
AI capability — Limited: AI assistance exists but is Pro-only, so it is unavailable in the free edition.
Schema tooling — Good: Genuinely good ER diagramming — one of its strengths — plus schema comparison in Pro.

pgAdmin

The official PostgreSQL admin tool. One engine, free forever, and it knows that engine better than anything else here.

Engine breadth — None: PostgreSQL only — plus Postgres-compatible engines by accident of the wire protocol. That is the entire point, and it is why it exposes Postgres internals nothing else does.
Cost & openness — Strong: Free and open source under the PostgreSQL Licence, with no paid tier at all. Nothing is held back.
Platform reach — Strong: Windows, macOS and Linux as a desktop app, plus a server mode you can host and use from a browser — the only tool here that does both well.
Production safety — Limited: Role and permission management is excellent, but that is database-side administration. The client itself will happily run whatever you type.
AI capability — None: None.
Schema tooling — Good: An ERD tool and a schema diff that produces a change script — both solid, both Postgres-only.

MySQL Workbench

The official MySQL tool, and still the best data modeller in this comparison — for exactly one engine.

Engine breadth — None: MySQL, and MariaDB to the extent the two stay compatible. Nothing else.
Cost & openness — Strong: Free and open source under GPLv2. A commercially licensed edition exists for organizations that need it, but the free build is the one nearly everyone uses.
Platform reach — Good: Windows, macOS and Linux. The interface shows its age, and the macOS build in particular feels dated next to newer clients.
Production safety — Limited: Safe Updates mode refuses UPDATE and DELETE without a key-based WHERE clause — a genuinely good guardrail, and one of the oldest examples of the idea. It stops there.
AI capability — None: None.
Schema tooling — Strong: The best schema tooling here for its engine: real EER modelling, forward and reverse engineering, and schema synchronisation between a model and a live database. Shipping since the mid-2000s and still the reference implementation.

Bytebase

Not a desktop client. A database DevOps and governance platform your team deploys — and the strongest answer here to "who approved this change?"

Engine breadth — Good: Around 20 engines, weighted towards the ones organizations run in production rather than breadth for its own sake.
Cost & openness — Good: A free Community tier covering up to 20 users and 10 database instances, self-hostable including air-gapped. Pro is $20/user/month; Enterprise is custom. Source is on GitHub, though not all of it is under an open-source licence.
Platform reach — Limited: Web-based, self-hosted or cloud. There is no desktop app — you reach it through a browser, which is a different daily workflow from everything else in this table.
Production safety — Strong: The strongest production safety story on this page, and it is not close: change review with custom approval workflows, dynamic data masking, an audit trail of who ran what, and policy enforcement before a change reaches production. It is built for the compliance question, not the convenience one.
AI capability — Limited: Some AI-assisted SQL, but AI is not what the product is about.
Schema tooling — Strong: Schema migration and version control is the entire product — GitOps-style change management, drift detection, and a review pipeline for database changes. Nothing else here treats migrations as the main event.

Pluk

An AI-native client built around a notebook agent. The most ambitious AI story here, on the narrowest foundation.

Engine breadth — Limited: PostgreSQL, MySQL, SQLite and MongoDB, plus Convex, Supabase and Neon. A deliberately small set aimed at the modern application stack.
Cost & openness — Good: A free tier with up to 4 connections and limited AI usage; Pro is $15/month for unlimited connections and the full Notebook Agent. A Team tier is planned. Not open source.
Platform reach — Limited: macOS only today. Windows and Linux are on the roadmap, which rules it out for a mixed-OS team right now.
Production safety — Limited: The AI is scoped to table and column names rather than row data, and generated queries are reviewable before they run — a thoughtful privacy boundary. There are no production write guards beyond that.
AI capability — Strong: The most agentic approach here: describe a report and the Notebook Agent explores the schema and builds a working draft, with every step editable. Where other tools bolt AI onto a client, this is a client built around the agent.
Schema tooling — Limited: Browsing and structure viewing. Schema change management is not the focus.

Dory

An Apache-2.0 SQL workspace built for humans and coding agents to share. The only tool here where an external agent is a first-class user.

Engine breadth — Good: Twelve SQL engines — Postgres (with Neon and Supabase), MySQL, MariaDB, SQLite, Cloudflare D1, DuckDB, SQL Server, Oracle, Snowflake and a deeply integrated ClickHouse — plus local CSV, TSV, Parquet, JSON and Excel files read through DuckDB. All SQL: no Mongo, Redis, Cassandra or Neo4j, and no BigQuery, Redshift or Databricks.
Cost & openness — Strong: Apache-2.0 and free, with nothing sold: no pricing page, no paid edition, commercial use included. Self-host it with Docker or run the desktop build. The hosted service carries hobby/pro plumbing and an AI token quota that a deployment can switch on, but a self-hosted install with your own key has neither.
Platform reach — Good: macOS and Windows desktop builds, a self-hosted web app over Docker, and an npm CLI that doubles as the agent runtime. No Linux desktop app — on Linux you self-host and use the browser.
Production safety — Limited: The safety thinking is aimed at the agent rather than at you: agents get read-only SQL, and their work lands as an inspectable workspace to review before you act on it, which is a better answer than a chat transcript. For your own statements there is nothing — no read-only connections, no statement classification, no production tag.
AI capability — Strong: Schema-aware SQL generation, rewriting and explanation, bring-your-own-key across OpenAI, Anthropic, Google, Qwen, xAI and any OpenAI-compatible endpoint. The distinctive part is MCP: Claude Code or Codex can use Dory as their database execution layer, and what the agent did comes back as editable SQL tabs, result sets and charts. One caveat their README states plainly — AI requests are the exception to everything staying on your machine, routed through a Cloudflare AI gateway; it is a per-deployment setting, so self-hosting with your own key is how you avoid it.
Schema tooling — Limited: An interactive schema graph of primary keys, foreign keys and relationships, with PNG and SVG export — genuinely good for learning an unfamiliar database. There is no schema diff and no migration tooling, so getting a change to production is not something it helps with.

Head-to-head comparisons

AddisDB vs DBeaver — The most widely used open-source database client, and the broadest engine support of anything on this page.
AddisDB vs JetBrains DataGrip — A database IDE. The best SQL editor of the group, priced and shaped like a developer tool rather than a database browser.
AddisDB vs TablePlus — The fastest, most native-feeling client here, sold once rather than rented. Deliberately minimal.
AddisDB vs QoreDB — The closest thing to AddisDB on this page: Rust and Tauri, local-first, SQL and NoSQL, with a diff-before-you-commit workflow — and open source.
AddisDB vs Beekeeper Studio — A clean, friendly, open-source client that does the everyday things well and does not try to be an IDE.
AddisDB vs DbVisualizer — A long-established cross-platform client with strong diagramming, where most of what you want is behind the Pro edition.
AddisDB vs pgAdmin — The official PostgreSQL admin tool. One engine, free forever, and it knows that engine better than anything else here.
AddisDB vs MySQL Workbench — The official MySQL tool, and still the best data modeller in this comparison — for exactly one engine.
AddisDB vs Bytebase — Not a desktop client. A database DevOps and governance platform your team deploys — and the strongest answer here to "who approved this change?"
AddisDB vs Pluk — An AI-native client built around a notebook agent. The most ambitious AI story here, on the narrowest foundation.
AddisDB vs Dory — An Apache-2.0 SQL workspace built for humans and coding agents to share. The only tool here where an external agent is a first-class user.

Why maturity is not one of the columns

Every table like this one has an unspoken seventh column: how long the thing has existed. On that axis this is not a contest. pgAdmin has been around since the late 1990s. MySQL Workbench descends from tools that predate most of the databases on this page. DBeaver has been collecting bug reports from people pointing it at strange, broken, enterprise-shaped databases since 2010. AddisDB has a small fraction of that history.

We left it out of the table because a number that AddisDB cannot win no matter what it does would quietly decide the whole comparison, and because age measures how long a tool has existed rather than whether it does the job you need today. But leaving it out is self-serving, so here is the honest version of the argument in both directions.

Where maturity genuinely matters

Edge cases. A long-established client has met the weird collation, the ancient Oracle version, the driver that lies about its types. A new one has not.
Answers. When something breaks at 2am, a mature tool has a decade of Stack Overflow questions behind it. A new tool has a support inbox.
Institutional trust. If you need to justify the choice to a security review, "in production at thousands of companies since 2010" is an argument. A short track record is not.
Longevity. Tools die. An established one with a paying customer base is a safer ten-year bet than a young one, and that is a real consideration for something you build habits around.

Where it misleads

It is not a proxy for the features in this table. Production guardrails and plain-English SQL are recent ideas; being old is if anything a reason a tool does not have them, because the architecture predates the problem.
It rewards accumulation, not fit. A tool can be decades old and still make schema changes to prod a leap of faith, because nothing forced it to change.
It is not the same as stability. Being old and being maintained are different claims, and some long-lived database tools are effectively feature-frozen.

So: weigh it, but weigh it as its own thing rather than letting it stand in for capability. If your requirement is a tool that has survived a decade of production use, that requirement is legitimate and it rules AddisDB out today. If your requirement is that the client stops you dropping a column on a Friday, age will not tell you which of these does that.

Sources

Every price and capability above came from the vendor's own pages, checked 2026-08-11.