Most projects aren't just Postgres. There's a relational database for the core data, a document store for flexible records, and a key-value cache in front of it. TableHub is a free, cross-platform AI database workspace that puts PostgreSQL, SQLite, MongoDB, and Redis side by side — in one window.
If you run a typical modern stack, your desktop probably looks like a graveyard of single-purpose tools: one GUI for Postgres, MongoDB Compass for your documents, RedisInsight for your cache, and something else for that SQLite file. Each has its own connection manager, its own quirks, its own keyboard shortcuts to relearn. You spend real minutes every day just finding the right window.
TableHub collapses that into a single workspace. Add a PostgreSQL connection, a MongoDB connection, and a Redis connection, and they all live in the same sidebar. You inspect a relational table, jump to a document collection, and peek at a cached key without ever leaving the app or breaking your train of thought. The result is one mental model instead of four — the same browse, query, and edit flow whether the data underneath is rows, documents, or keys.
This matters most when you're debugging across layers. A bug that shows up in the app is often "the row in Postgres is right, but the cached value in Redis is stale, and the document in Mongo never got updated." Chasing that across three separate applications is slow and error-prone. Seeing all three next to each other is how you actually find it.
| Database | Type | In TableHub |
|---|---|---|
| PostgreSQL | Relational | Yes |
| SQLite | Embedded | Yes |
| MongoDB | Document | Yes |
| Redis | Key-value | Yes |
Two SQL engines and two NoSQL engines, covering the shapes most applications actually use: relational tables, an embedded file database, a document store, and an in-memory cache. You connect to each the same way, and each shows up as a first-class citizen in the same tree.
The part that ties SQL and NoSQL together is the built-in AI agent — and it isn't bolted on to just the SQL side. It works across every engine TableHub supports, in both directions.
Describe what you want in natural language and the agent produces the query in the right dialect for the database you're on. Ask for "users created in the last 7 days" against Postgres and you get SQL; ask for "orders over $100 grouped by status" against MongoDB and you get an aggregation pipeline; ask about a cache pattern against Redis and you get the matching commands. You don't have to context-switch your own head between query languages — the agent does it.
Just as important, it reads queries back to you. Paste a gnarly MongoDB aggregation you inherited and the agent walks you through each stage in plain English. Point it at an unfamiliar Redis command and it tells you exactly what that command does and why it's there. The same holds for a dense SQL statement full of joins and window functions. This is how a NoSQL query language you rarely touch stops being a wall — the agent translates it into something you can reason about.
That two-way understanding, native to the workflow across both SQL and NoSQL, is what makes a single client genuinely usable when your databases don't all speak the same language.
You don't even need an existing database to start. TableHub can spin up a local PostgreSQL, MongoDB, or Redis instance for you with one click, using Docker under the hood (Docker needs to be installed and running). That's genuinely useful when you want to prototype against a document store, try a caching pattern, or reproduce a bug in isolation without touching shared infrastructure.
So the loop is complete: create the database, connect to it, and query it — SQL or NoSQL — all inside one app. See Docker local databases for the details on how the one-click spin-up works.
And once you have results, built-in charts turn any query output into a visualization inline, so you can see a trend instead of scrolling a grid of numbers — no export to a separate tool required.
To be fair, TableHub is not the only free client that spans SQL and NoSQL. DbGate is a genuinely good open-source option that also connects to relational and document databases in one place — if all you need is a free unified browser and query editor, it's a real and capable choice, and we'd rather you know that than be misled.
Where TableHub differs comes down to two things. First, TableHub can create the database for you: the one-click Docker spin-up means you're not only browsing existing connections, you can stand up a fresh Postgres, MongoDB, or Redis in seconds. Second, the AI agent is native to the workflow rather than an afterthought — writing and explaining queries across SQL and NoSQL is built into the same panel you're already working in. If those two things matter to you, that's the honest edge; if they don't, DbGate is a perfectly reasonable pick.
Yes. TableHub supports NoSQL and SQL together in one app. For NoSQL it works with MongoDB (document) and Redis (key-value); for SQL it works with PostgreSQL (relational) and SQLite (embedded) — all side by side.
Yes. PostgreSQL, SQLite, MongoDB, and Redis live in a single client at the same time. You can keep a Postgres, a Mongo, and a Redis connection open together and switch between them without launching a second application.
Yes. The built-in AI agent spans both SQL and NoSQL. It writes queries from natural language and explains existing ones in plain English — including MongoDB aggregation pipelines and Redis commands, not just SQL.
Yes. TableHub is free and cross-platform on macOS, Windows, and Linux. There's no per-database pricing — SQL and NoSQL support, the AI agent, and built-in charts are all included.
See also: Docker local databases · AI database agent · MongoDB Compass alternative · RedisInsight alternative