Meet CreamDB: Every Database in One Browser Tab, With AI Built In

It is 11 p.m. and a customer says their order has vanished. The answer is sitting in three places: an orders table in PostgreSQL, a session in Redis, and an event log in MongoDB.

So you open pgAdmin. Then MongoDB Compass. Then a Redis client. Your laptop fan starts to spin, one of the three wants an update before it will start, and you still have not written a single query.

If that sounds familiar, this post is for you. It explains why working with data still feels harder than it should, and how we built CreamDB to fix it.

The data is there. Getting to it is the hard part.

Every company says data is its most valuable asset. Yet the everyday act of looking at it is still slow, and the reasons have barely changed in fifteen years.

1. One workbench per database

PostgreSQL has pgAdmin. MySQL has Workbench. MongoDB has Compass. SQL Server has SSMS. Redis, Kafka, Elasticsearch and S3 each bring their own tool too.

A typical product today uses four or five data stores. That means four or five apps to install, update and learn, each with its own shortcuts, its own way of saving connections, and its own idea of where the "run" button lives. Your attention goes to switching tools instead of answering the question.

2. Heavy software that slows your machine

Most database tools are large desktop programs. Several of them are entire web browsers wrapped in an installer. Run three at once next to your editor, your browser and a few containers, and a perfectly good laptop starts to lag.

You notice it most at the worst time: during an incident, when you need everything open together.

3. Interfaces from another decade

Many of these tools were designed when a database had twenty tables and one administrator. The screens show it: deep menus, tiny icons, dialogs inside dialogs, and settings nobody can find twice.

New team members pay the highest price. They know what they want to ask, but they lose an hour learning where to click.

4. Software that breaks

Anyone who has used database tools for long has a list: the update that would not open old connections, the driver that stopped working after an operating system upgrade, the app that froze on a large result and took unsaved queries with it.

A tool you cannot trust in an emergency is not really a tool.

5. No AI, in the age of AI

This is the strangest gap. In 2026 we ask AI to write code, summarise meetings and review contracts. But to ask a database "which customers ordered twice last month?", most people still have to remember the join syntax, look up column names, and assemble the query by hand.

Some teams paste their schema into a chatbot and copy the SQL back. It works, but it is clumsy, and it puts your table structure into a chat window that knows nothing about your database.

What this really costs

Add these up and something worse happens than wasted minutes: people stop asking questions.

The product manager waits two days for an engineer to run a query. The founder decides on instinct because the dashboard does not cover this case. The support agent says "we are looking into it" when the answer was one query away.

Data that is hard to reach gets used less. That is the real problem we set out to solve.

What CreamDB is

CreamDB is a database workspace that runs in your browser. You open one tab, connect your databases, and work with all of them in the same place. There is nothing to install.

It has an AI assistant built in, so you can ask a question in plain English and get the SQL, a table of results and a chart back.

Here is how it answers each of the five problems.

One workspace for 40+ databases

PostgreSQL, MySQL, MariaDB, SQL Server, Oracle, SQLite-compatible libSQL, ClickHouse, Snowflake, BigQuery, Redshift, CockroachDB and more sit side by side in one connection tree.

It is not limited to SQL. MongoDB, Redis, Elasticsearch, Neo4j, Kafka, RabbitMQ, InfluxDB, Amazon S3 and others each get a purpose-built explorer in the same window: documents for MongoDB, keys for Redis, topics for Kafka, buckets for S3.

Same tabs, same shortcuts, same export button, whatever is on the other end.

Nothing to install, nothing to slow you down

CreamDB is a web page. The heavy work, connecting to your database and running queries, happens on our servers, so your laptop only has to draw the result.

That also means it works on any device. Open it on a borrowed computer, a tablet or your phone, sign in, and your connections and open tabs are waiting. You can also install it as an app from the browser if you like having an icon to click.

An interface built for today

The workspace has a proper SQL editor with autocomplete, formatting and query history. Tables open in a grid with real paging, sorting and filtering that run in the database, not in your browser, so a table with ten million rows opens as quickly as one with ten.

You can edit cells and review every change before it is saved, export results to CSV, JSON or Excel, view an ER diagram of your schema, watch live server status, and see which users and roles exist. Each of these is one click from the table you are looking at.

Always up to date, because there is no update

There is no installer, so there is no version to fall behind on and no driver to break after an operating system upgrade. When we fix a bug or add a database, you have it the next time you open the tab.

AI that knows your schema

Type a question the way you would ask a colleague:

Which five products earned the most revenue last quarter, and how does that compare with the quarter before?

The assistant reads your schema, writes the SQL, runs it, and replies with the query, the result and a chart. You can see and edit the SQL, so it also works as a patient teacher when you are learning.

It works beyond SQL as well. Ask it to build a MongoDB aggregation, find a Redis key, or search your logs.

You choose the model, DeepSeek or Claude, and if you already have your own AI key you can plug that in instead.

Careful by design

Giving an AI access to a database is a serious thing, so we were strict about it.

• The assistant can only read on its own. Anything that changes data becomes an approval card that you answer. For risky statements such as DROP or a DELETE without a filter, you must type the name to confirm.
• Read-only mode is enforced on the server. Switch it on and nothing can write to your database: not you by accident, and not the AI.
• Your connection passwords are encrypted before they are stored, and the app never shows them again.
• Two-factor authentication is available for your account.
• Private databases stay private. Connect through an SSH tunnel instead of opening a port to the internet.

How to start

It takes about two minutes.

1. Go to www.creamdb.com and create a free account. Every new account gets a 30-day Mango trial with 3 million AI tokens, and no card is needed.
2. Click New Connection. Paste a connection string and CreamDB fills in the form for you, or enter the host and password yourself.
3. Open the AI panel and ask your first question.

The free plan, which we call Vanilla, stays free: it includes five connections and a monthly AI allowance. Paid plans start at $5 a month, or ₹425 if you pay from India.

What comes next on this blog

This is the first post of a long series. Over the coming weeks we will publish a practical guide for every database CreamDB supports: what each one is good at, when to choose it, how to use it well, and the mistakes worth avoiding.

We will also cover the problems every team meets sooner or later: connections that refuse to open, corrupted data and how to recover, database security, and how to turn the data you already have into decisions.

The aim is the same in every post: knowledge you can use the same day, whether or not you ever use our product.

If you would like to see your own data the easy way, try CreamDB free. Ask your database. Get the scoop.