XAMPP is a completely free, easy to install Apache distribution containing MariaDB, PHP, and Perl. The XAMPP open source package has been set up to be incredibly easy to install and to use.
The goal of XAMPP is to build an easy to install distribution for developers to get into the world of Apache. To make it convenient for developers, XAMPP is configured with all features turned on. In the case of commercial use please take a look at the product licenses, from the XAMPP point of view commercial use is also free. There are currently distributions for Windows, Linux, and OS X.
Add dynamic content, forms or personalization to your static site, manage smart home, monitor server room temperatures in hundreds of locations using Raspberry Pi, or simply play with the API - JsonStorage is super simple and scales up to your needs.
Investbrain is a Laravel PHP web application that leverages Livewire and Tailwind for its frontend. Most databases should work, including MySQL and SQLite. Out of the box, we feature three market data providers: Yahoo Finance, Finnhub, and Alpha Vantage. But we also offer an extensible market data provider interface for intrepid developers to create their own! We also offer an integration with OpenAI's LLMs for our "chat with your holdings" capability. Finally, of course we have robust support for i18n, a11y, and dark mode.
Looks like you can pull docker/Dockerfile apart and figure out how to run it outside of Docker.
BookBrainz is a project to create an online database of information about every single book, magazine, journal and other publication ever written. We make all the data that we collect available to the whole world to consume and use as they see fit. Anyone can contribute to BookBrainz, whether through editing our information, helping out with development, or just spreading the word about our project.
If you have a Musicbrainz account, it uses the same credentials.
DbGate is cross-platform database manager. It's designed to be simple to use and effective, when working with more databases simultaneously. But there are also many advanced features like schema compare, visual query designer, chart visualisation or batch export and import.
Supports MySQL, PostgreSQL, SQL Server, Oracle, MongoDB, Redis, SQLite, Amazon Redshift, CockroachDB, MariaDB, CosmosDB (Premium), ClickHouse. Admin databases, tables, schemas, indexes, keys. Synchronize database structures. Query designer. Form view. Limited JSON views.
A huge collection of IR remote control databases for the Flipper Zero. Covers an amazing array of devices, from master remote controls for hotels to laser disc players to bidets.
Simple self-hosted music scrobble database to create personal listening statistics. You will always be able to access your data in an easily-parseable format. Your library is not synced with any public or official music database, so you can follow your own tagging schema. Some artists often collaborate with others or are listed under "featuring" in the track title. Instead of tracking each combination of artists, each individual artist competes in your charts. Don't rely on the community to select the best pictures for your favorite artists. Upload your own so that your start page looks like you want it to look. No need to fully commit or set up every client twice - you can configure your Maloja server to forward your scrobbles to other services.
Use existing, mature apps or extensions to scrobble to your Maloja server. Manual scrobbling is possible, also.
Protip: If your MP3s don't have ID3 metadata, you won't see what you expect to see.
A plugin to take your published Pelican posts and put them into a SQLite database.
Once the plugin has been installed you only need to run make html to create a SQLite database called pelican.db which will be created in the root of your pelican site. There are partial instructions for using this to implement search for a site built with Pelican.
DO exposes performance metrics for hosted databases from their API. This talks about how to access them programmatically.
DrawDB is a robust and user-friendly database entity relationship (DBER) editor right in your browser. Build diagrams with a few clicks, export sql scripts, customize your editor, and more without creating an account.
Home of the world's largest radio/scanner frequency database. Celebrating 28 years of no ads and no subscriber fees.
This service dates back to the BBS days.
Embeddings databases are a union of vector indexes (sparse and dense), graph networks and relational databases. This enables vector search with SQL, topic modeling, retrieval augmented generation and more. Embeddings databases can stand on their own and/or serve as a powerful knowledge source for large language model (LLM) prompts.
Features
- Vector search with SQL, object storage, topic modeling, graph analysis and multimodal indexing
- Create embeddings for text, documents, audio, images and video
- Pipelines powered by language models that run LLM prompts, question-answering, labeling, transcription, translation, summarization and more
- Workflows to join pipelines together and aggregate business logic. txtai processes can be simple microservices or multi-model workflows.
- Build with Python or YAML. API bindings available for JavaScript, Java, Rust and Go.
- Run local or scale out with container orchestration
Also known as SQL for Data Scientists in 100 Queries.
Has its own pack of lesson materials (SQLite databases) here: https://github.com/gvwilson/sql-tutorial/raw/main/sql-tutorial.zip
Weaviate is an open source vector database that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
With Weaviate, you can turn your text, images and more into a searchable vector database using state-of-the-art ML models. Weaviate typically performs a 10-NN neighbor search out of millions of objects in single-digit milliseconds. You can use Weaviate to conveniently vectorize your data at import time, or alternatively you can upload your own vectors (say, if you download a model from OpenAI or HuggingFace). Weaviate powers lightning-fast vector searches, but it is capable of much more. Some of its other superpowers include recommendation, summarization, and integrations with neural search frameworks.
cve-maker is a hub for finding CVEs and exploits. It is based on the official NIST, ExploitDB and Github databases. The tool makes it quick and easy to search for CVEs and their associated exploits. It is able to detect exploit compilation options. It can also be used to list the latest critical vulnerabilities.
Canonical’s Security Team produces Ubuntu OVAL, a structured, machine-readable dataset for all supported Ubuntu releases. It can be used to evaluate and manage security risks related to any existing Ubuntu components. It is based on the Open Vulnerability and Assessment Language (OVAL).
Ubuntu OVAL also allows for any third-party Security Content Automation Protocol (SCAP) compliant tools to accurately scan an Ubuntu system or an official Ubuntu OCI image for vulnerabilities.
wget https://security-metadata.canonical.com/oval/com.ubuntu.$(lsb_release -cs).usn.oval.xml.bz2
Public api for aircraft, airlines, and flight routes. No API key, everything is rate limited over a 60 second period.
I don't know how useful or reliable it is yet.
SponsorBlock is an extension that will skip over sponsored segments of YouTube videos. This is the server backend for it. Uses a Postgres or Sqlite database to hold all the timing data.
To make sure that this project doesn't die, I have made the database publicly downloadable at https://sponsor.ajay.app/database. You can download a backup or get archive.org to take a backup if you do desire. The database is under this license unless you get explicit permission from me.
In the spirit of Feynman's immortal words, the goal of this project is to better understand the internals of databases by implementing a relational database management system (RDBMS) (sqlite clone) from scratch.
This project was motivated by a desire to: 1) understand databases more deeply and 2) work on a fun project. These dual goals led to a:
- relatively simple code base
- relatively complete RDBMS implementation
- written in pure python
- No build step
- zero configuration
- configuration can be overridden
This makes the learndb codebase great for tinkering with. But the product has some key limitations that means it shouldn't be used as an actual storage solution.