A native database IDE for SQL, document, and vector backends, with an assistant grounded in your real schema. Here is the whole tour.
Natural language, SQL, or your database's own language. Write a query however you think about it, and SnoutData runs it as what the database actually executes, across relational, document, and vector backends like PostgreSQL, MongoDB, and Pinecone.
Tell the assistant what you want. It reads your live schema and writes a runnable query: SQL for relational databases, or a native aggregation pipeline for MongoDB.
SQL is the lingua franca. Write it against MongoDB or a Pinecone index and SnoutData transcribes it to a native aggregation pipeline or vector query, exact and offline for the common shapes, with the assistant covering the rest.
Drop into MongoDB's aggregation-pipeline editor for the full expressive range, with schema-aware completion. Same results grid, same workflow as SQL.
One IDE, one assistant, across relational, document, and vector backends. More engines land regularly.
Everything you expect from a pro database client, plus an assistant that understands what it is looking at.
Relational, document, and vector databases, all with the same editor, results grid, and assistant. Connect to engines like PostgreSQL, MySQL, MongoDB, and Pinecone, with more on the way.
The assistant reads your live tables, columns, fields, and foreign keys, so it drafts queries that fit your database, whether that is SQL or a MongoDB aggregation pipeline, instead of generic guesses.
We hand a smaller, well-tuned model exactly the tables your question touches, so it stays precise without burning a frontier model on everyday queries. No crawling your whole database, no wasted tokens, just faster and cheaper answers.
Browse millions of rows or documents with server-side paging, edit cells inline, and manage tables, collections, and indexes with a preview that runs on confirm.
A native desktop app, not a browser tab. Passwords and SSH keys are encrypted in your OS keychain, never in config files.
On Plus and Pro, point the assistant at your own Claude, ChatGPT, or any OpenAI-compatible model. Your key and prompts go straight to the provider and never touch our servers.
Let Claude Code, Codex, or any MCP client query your databases through SnoutData. The agent gets read-only access by default, never your passwords or keys, and only the connections you allow.
Production connections are flagged, destructive statements ask for confirmation before they run, and every query you run is logged.
Most tools paste your prompt into a generic model and hope. SnoutData ranks the tables most relevant to your question, follows their foreign keys, and grounds the model in your real columns and types, so the query it writes actually runs, whether that is SQL or a MongoDB aggregation pipeline.
select p.name from products p left join orders o on o.product_id = p.id and o.created_at > now() - interval '90 days' where o.id is null;
A real desktop database IDE with an assistant that understands your data. Here is what that looks like.
The assistant reads your live schema (tables, columns, foreign keys), writes real runnable SQL, and explains its reasoning. One click drops it into the editor or a new tab.
Start typing and Snout Complete suggests the rest inline. Press Tab to accept. This is our own FIM model (snout-fim-1.0), not the deterministic keyword list, served through our gateway so the suggestion fits your actual schema.
Snout Complete adapts to how you build SQL. As you write queries it learns your patterns, your formatting, the columns and filters you reach for, and folds that into its inference, so the suggestions get closer to exactly what you would have typed instead of a generic average.
Expand the chat to a focused full-window view and let it work as an agent: it runs queries against your database, reads the results, and keeps the thread going. Pick the model and how much freedom it gets.
Hand it the error and the SQL that produced it. It diagnoses the cause against your actual schema, a wrong table name or a missing column, and returns corrected SQL.
Point the assistant at a slow table and ask. It reads the real indexes and column stats, then recommends the exact CREATE INDEX statements, each with the why, the impact, and the trade-offs, and drops them into the editor ready to run.
Each table gets a telemetry view: storage and index sizes, schema facts like keys, indexes, engine, and collation, plus the queries that recently touched it.
Relational, document, and vector backends, with engines like MySQL and Aurora, PostgreSQL, SQL Server, MongoDB, and Pinecone. Optional SSH tunneling and AWS Secrets Manager. Credentials are encrypted by your OS keychain, never stored in plain text.
On Plus and Pro, point the assistant at your own OpenAI, OpenRouter, or Anthropic key. Requests go straight to that provider, so your key and prompts never touch our servers, and the key is encrypted in your OS keychain.
Point Claude Code, Codex, or any MCP client at your databases through SnoutData. Your passwords and keys never leave your OS keychain, and never touch the agent or a repo. Access is read-only by default, and you pick exactly which connections are reachable.
Some questions are easier to read as a picture. Ask for one and the assistant runs the query and renders the chart right in the thread, ready to save. No spreadsheet round-trip.
Build a dashboard of live widgets, each a SQL query that refreshes on its own interval and plots over time. Trend charts, tables, and bar charts keep polling across every connection while you work, so you watch your database move instead of re-running queries by hand.
A polished light theme and a deep dark theme, both tuned for long sessions staring at query results.
Download SnoutData and let the assistant learn your schema in seconds.