Data Panda reads the SQLite databases that sit inside desktop tools, mobile apps, scientific software and embedded devices, and writes them next to the rest of your data. The single .db or .sqlite file stops being an island, and the records it holds join customers, orders and finance in one warehouse.
SQLite is an in-process SQL database engine written in C, started by D. Richard Hipp on 9 May 2000 and maintained today by an international team at Hwaci with a public pledge to support the format through 2050. The whole database lives in a single cross-platform file, the engine is a library that links into the host process, and the source code is dedicated to the public domain (not an OSI license, an explicit dedication) so anyone can ship it anywhere without paperwork. The library is under 900 KiB with all features enabled, ACID-compliant even across power loss, and the US Library of Congress lists it as a recommended storage format for long-term archival.
The deployment scale is the part that surprises people. SQLite is the most widely deployed database engine in the world, embedded in every Android and iOS device, every Mac and Windows install, every Firefox, Chrome and Safari browser, and inside Adobe Lightroom, Dropbox, QuickBooks, TurboTax, Skype, Airbus A350 flight software and most car multimedia systems. The official site puts the active count at over a trillion databases in the wild. In a business context that means SQLite is rarely the warehouse, but it is very often the system-of-record for one specific tool: a desktop ERP, a scientific instrument's logger, a mobile-first app's local store, a metadata catalog inside a vendor product. Pulling that file into the warehouse is how the data inside it joins the rest of the stack.
The SQLite file behind a desktop ERP, CAD or finance tool joins the warehouse so its records show up next to CRM and accounting.
A mobile app's local SQLite store, exported or synced to a backend, becomes a source the warehouse can act on.
Lab software, sensors and instruments often log into SQLite. We land that file in the warehouse so models and notebooks reach it.
When the eventual destination is DuckDB, Postgres or a real warehouse, SQLite is the source you start from.
A list of concrete reports, automations and AI features we have built on SQLite data. Pick the one that matches your situation.
Why would we pull SQLite into a warehouse at all?
Because the SQLite file usually sits inside one tool and the data inside it is invisible to the rest of the business. A desktop ERP, a CAD package, a scientific instrument or a mobile app holds its records in a .sqlite or .db file that nothing else queries. Loading that file into the warehouse joins the records to CRM, accounting, ecommerce and operational sources, so reporting and automation stop depending on someone opening the app.
Is SQLite a real database or just a file format?
It is a real ACID-compliant SQL database engine that happens to store its data in one cross-platform file. The official guidance is that SQLite competes with fopen(), not with Postgres or MySQL: it is the right choice for in-process, single-writer workloads on a device. For multi-writer, network-attached, multi-user workloads, a client-server database is the right tool, which is why SQLite is the source we lift into the warehouse and not the warehouse itself.
What is the difference between SQLite and DuckDB for our use case?
SQLite is row-oriented and built for transactional reads and writes on one device, so it is the format you find inside operational tools and apps. DuckDB is columnar and built for analytical SQL, which makes it the format you reach for at the analysis end. In practice the two often pair up: SQLite is the source-of-truth inside a tool, DuckDB or a warehouse is where you join it to the rest of the data.
Finance gets the records out of the desktop accounting or ERP tool that holds them in a .sqlite file, joined to the bank data, the CRM and the rest of the stack in the warehouse. Reconciliation works on warehouse tables instead of an export-of-an-export from one machine.
Sales and field teams using mobile-first apps see the data they capture in SQLite on the device end up in the central warehouse next to the back-office data. One view spans what was logged offline on the road, what the office systems already knew, and which accounts to call next.
Operations teams stop chasing screenshots from a desktop tool that no one else can open. The SQLite file behind that tool lands in the warehouse on a schedule, the records show up next to CRM and finance, and the daily report no longer hangs on whether the right laptop is on.
You keep the reporting tool you already have. We connect it to the warehouse where your SQLite data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
SQLite is in-process: it lives as a library inside the application that uses it, with no separate server, no port to open and no users to manage. The whole database is one cross-platform file. Postgres and MySQL are client-server databases: they run as a daemon, accept network connections, handle many concurrent writers and ship with role and grant systems. SQLite is the right answer when one device or one process owns the data; Postgres and MySQL are the right answer when many writers across the network need the same database. SQLite is what we typically lift into the warehouse, not what we use as the warehouse.
SQLite is open source in the everyday sense (you can read, modify and ship the code freely), but it is explicitly placed in the public domain rather than under a license like MIT, Apache or GPL. Contributors sign affidavits dedicating their work to the public domain so the code base stays unencumbered. For organisations that need a paper trail (some jurisdictions do not formally recognise public-domain dedication), Hwaci sells a Warranty of Title that funds further development; the code itself remains free.
Yes. The official site claims SQLite is the most widely deployed database engine in the world, with over a trillion active databases. It is embedded in every Android and iOS device, every Mac and Windows install, every Firefox, Chrome and Safari browser, and inside Adobe Lightroom, QuickBooks, TurboTax, Dropbox, Skype, the Airbus A350 flight software and most car multimedia systems. The US Library of Congress lists it as a recommended long-term archival format. The practical takeaway is that SQLite files often hold business-critical data without anyone having decided to use SQLite; the application picked it.
We review your SQLite setup and the systems around it. Together we pick the first thing worth building.