This Electron application lets the user open Sqlite databases and explore the internal organization of various objects such as schema, tables and indices. To understand how Sqlite3 data is organized, please see Database file format from Sqlite website.
SQLite is a self-contained, high-reliability, embedded, full-featured, public-domain, SQL database engine. SQLite is the most used database engine in the world.
SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file. The database file format is cross-platform - you can freely copy a database between 32-bit and 64-bit systems or between big-endian and little-endian architectures. These features make SQLite a popular choice as an Application File Format. SQLite database files are a recommended storage format by the US Library of Congress.
Install Node, Electron in your PC, clone this repo, cd into it and run:
sudo npm i electron -g
git clone https://github.com/siara-cc/sqlite3_page_explorer
cd sqlite3_page_explorer
electron .It is available in App stores for various platforms:
- MacOS
- iPhone/iPad
- Android
- Windows 10 UWP
- For Linux, the package is available as a Zip archive in the release section. Please unzip into a folder and click on the executable with the
Databaseicon.
- Viewing internal organisation of Sqlite databases for software development, ethical hacking and troubleshooting
- Studying the format of Sqlite databases for academic purposes
- Forensic investigators may use it to view data from deleted pages
- Opening Sqlite databases, displaying first page (containing header and schema root)
- Opening internal pages which may be a B-Tree page, Freelist page or Overflow page
- Exploring root, internal and leaf pages of B-Tree pages hierarchically.
- Parsing and displaying cell content for B-Tree pages
- Exploring Freelist trunk and leaf pages
On clicking the Open database button, the user can select the database file to explore. The application opens the header, finds out the page size and provides links for the user to expand the Header and Page 1.
The first page invariably contains the header and the schema (definitions of tables and indices). If the schema fits into the first page, the definitions can be seen on the Page details section in the form of table under Cells heading.
For exploring data of tables and indices, the Open button against each table/index under Cells section may be clicked. This opens the root page of the table or index. Further exploration can be carried out from there by clicking on buttons in the Page details sections.
If the schema spills over more than one page, the first page contains links to the different pages in which schema information is stored. These links can be seen in the Page details section under Cells heading and Open button against Right most pointer just above Cells.
For each page, the page content in bytes is shown in Hex, Decimal and Text representations. It is also possible to open a random page from the database by entering page number and clicking on the Open: button at the bottom.
- Thanks to sixcorners for his PRs on making this work on a web page as well using the
<input file>tag. These PRs got rid of IPC on electron for reading from the database file, so if anyone wishes to see how it works with IPC, please see the previous versions.
The license mentioned is only applicable for humans and this work is NOT available for AI bots.
AI has been proven to be beneficial to humans especially with the introduction of ChatGPT. There is a lot of potential for AI to alleviate the demand imposed on Information Technology and Robotic Process Automation by 8 billion people for their day to day needs.
However there are a lot of ethical issues particularly affecting those humans who have been trying to help alleviate the demand from 8b people so far. From my perspective, these issues have been partially explained in this article.
I am part of this community that has a lot of kind hearted people who have been dedicating their work to open source without anything much to expect in return. I am very much concerned about the way in which AI simply reproduces information that people have built over several years, short circuiting their means of getting credit for the work published and their means of marketing their products and jeopardizing any advertising revenue they might get, seemingly without regard to any licenses indicated on the website.
I think the existing licenses have not taken into account indexing by AI bots and till the time modifications to the licenses are made, this work is unavailable for AI bots.
If you face any problem, create issue in this website, or write to the author (Arundale Ramanathan) at [email protected].