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Varan
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Varan is a desktop SQL client for querying across different databases at once. Point it at MySQL, PostgreSQL, DuckDB, or spreadsheet files (CSV and Excel) and run a single SQL query โ including JOINs โ across all of them, without ETL pipelines or importing everything into one database first.
It runs on a local-first DuckDB engine, so queries execute on your own machine with read-only access to your sources: no admin rights, no server to set up, and nothing is written back to your databases.
Beyond cross-source SQL, Varan adds the tools data people always wish they had โ automatic anomaly detection when you open a table (duplicate keys, missing values, outliers, and orphaned foreign-key references), column-level lineage, git-style rollback of every change, and a Python surface on the same live tables you query in SQL.
Varan is a cross-platform desktop app for macOS, Windows, and Linux, currently in beta.
SQL Developer VaranVaran's answer:
Varan runs a single SQL query across different databases and files at once. Most SQL clients (DBeaver, DataGrip, TablePlus) connect to one database at a time; Varan lets you JOIN a MySQL table to a PostgreSQL table to a CSV in one statement, powered by a local-first DuckDB engine โ no ETL, no pipelines, no data copied into a warehouse first. On top of that it adds automatic anomaly detection, column-level lineage, and git-style rollback in the same workspace.
Varan's answer:
Data analysts, analytics engineers, and data-adjacent developers who regularly work across several databases and spreadsheets. People who can write SQL but aren't DBAs โ they have read-only access to production and don't want to spin up ETL pipelines or a warehouse just to answer an ad-hoc question spanning two systems.
Varan's answer:
Traditional SQL clients are single-database, so cross-source work means exporting and stitching data by hand. Federated engines like Trino or ClickHouse can query across sources but need infrastructure to stand up and manage. Varan sits in between: open a desktop app, point it at your sources (read-only, no admin), and query across all of them instantly โ with lineage, anomaly detection, and rollback built in. It's the convenience and workflow of a polished app on top of a serious engine, without the setup.
Varan's answer:
Varan started from a recurring frustration: whenever an answer needed data from two places โ a Postgres database, a MySQL host, and the inevitable sales_final.xlsx โ the options were to build an ETL pipeline, hand-write fragile pandas glue, or give up. We wanted to just point one tool at everything and write a normal JOIN. So we built Varan around a local-first DuckDB engine that queries across sources directly, and added the data-quality and versioning tools we always wished we had. It's currently in beta.
Varan's answer:
DuckDB (the local-first query engine) Electron + React (desktop application) Node.js (application/runtime layer) Python (bundled analysis surface) Java / Spring Boot (the licensing & sync hub backend) PostgreSQL (hub data store)
phpMyAdmin - phpMyAdmin is a tool written in PHP intended to handle the administration of MySQL over the Web.
DBeaver - DBeaver - Universal Database Manager and SQL Client.
DbVisualizer - DbVisualizer is the universal database client and SQL tool built for developers, analysts, DBAs, data engineers, and anyone working with data.
DataGrip - Tool for SQL and databases
Navicat - Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily.
TablePlus - Easily edit database data and structure