Open Source Mac Database Software - Page 20
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Database Software for Mac
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Hydra Columnar
Postgres-native columnar storage extension
Hydra Columnar is an open-source columnar storage extension for PostgreSQL designed to deliver analytics performance on par with modern data warehouses. It integrates seamlessly with the PostgreSQL ecosystem, allowing users to benefit from columnar compression, vectorized execution, and late materialization without leaving their existing database setup. Hydra enables hybrid row-column storage, making it ideal for OLAP workloads on Postgres. -
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IndraDB
A graph database written in rust
A graph database written in rust. IndraDB consists of a server and an underlying library. Most users would use the server, which is available via releases as pre-compiled binaries. But if you're a rust developer that wants to embed a graph database directly in your application, you can use the library. IndraDB's original design is heavily inspired by TAO, facebook's graph datastore. In particular, IndraDB emphasizes simplicity of implementation and query semantics, and is similarly designed with the assumption that it may be representing a graph large enough that full graph processing is not possible. IndraDB departs from TAO (and most graph databases) in its support for properties. IndraDB offers a variety ways to work with it: as a server with cross-language support, as a rust library, and via CLI. What follows are a few examples of each use case. -
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Infinispan
Infinispan is an open source data grid platform
Infinispan is a distributed in-memory data grid and caching system designed for high-performance computing. It allows applications to scale dynamically by distributing data across multiple nodes, reducing latency and improving resilience. -
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Jenkins Docker
Docker jenkins repo
The Jenkins Continuous Integration and Delivery server available on Docker Hub. The leading open source automation server, Jenkins provides hundreds of plugins to support building, deploying and automating any project. If you bind mount in a volume, you can simply back up that directory (which is jenkins_home) at any time. This is highly recommended. Treat the jenkins_home directory as you would a database, in Docker you would generally put a database on a volume. If your volume is inside a container, you can use a Docker command to extract the data, or other options to find where the volume data is. Note that some symlinks on some OSes may be converted to copies (this can confuse jenkins with lastStableBuild links etc). You can define the number of executors on the Jenkins built-in node using a groovy script. By default it is set to 2 executors, but you can extend the image and change it to your desired number of executors. -
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Jennifer
Crystal ORM using ActiveRecord pattern with flexible query DSL
ActiveRecord pattern implementation for Crystal with a powerful query DSL, validation, relationship definition, translation and migration mechanism. You need to choose one of the existing drivers for your DB: MySQL or Postgres; the sqlite3 adapter automatically installs the required driver for it. Jennifer allows you to maintain everything for your models - from DB migrations and field mapping to callbacks and building queries. For detailed information see the docs and API documentation. For command management Jennifer uses Sam. Due to this you can easily create/migrate/drop a database or invoke a generator to bootstrap your models and migrations. Jennifer has a built-in database migration management system. Migrations allow you to organize all database changes. -
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Jest Preview
Debug your Jest tests. Effortlessly
Jest Preview has a mission. To make front-end developers' life easier. It's built with the mindset of Developer Experience first in mind. Write tests in Jest and see the changes reflects in browser in a few milliseconds. You can use Jest Preview with any testing libraries and frontend frameworks. Don't waste time guessing what is your UI looks like. Let's Jest Preview visualize it in a browser for you! When writing tests using Jest, we usually debug by reading the HTML code. Sometimes, the HTML is too complicated to visualize the UI in our head. jest-preview previews your Jest tests right in a browser, then you can see your actual UI visually, which helps you write and debug Jest tests faster. jest-preview is initially designed to work with Jest and react-testing-library. The package is framework-agnostic, and you can use it with any frontend frameworks and testing libraries. -
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KCloud‑Platform‑IoT
KCloud-Platform-IoT
KCloud-Platform-IoT is a comprehensive open-source IoT management platform built with Spring Cloud and Vue.js. It supports device registration, data collection, rule-based processing, and dashboard visualization. Designed for scalability and modularity, the platform is ideal for managing large IoT fleets in industrial or smart city environments. -
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Kangaroo
Kangaroo is an AI-powered SQL client and admin tool for popular dbs
Kangaroo is an AI-powered SQL client designed to enhance database interaction by integrating large language model capabilities into query workflows. It allows users to write, analyze, and optimize SQL queries using natural language assistance, making database operations more accessible and efficient. The tool is intended for developers, analysts, and data professionals who want to simplify complex query generation and debugging processes. It integrates with databases to provide context-aware suggestions, helping users understand schema structures and relationships. Kangaroo also supports conversational querying, enabling users to describe what they want to retrieve and receive corresponding SQL queries. The system aims to bridge the gap between traditional database tools and modern AI-driven workflows. Overall, Kangaroo transforms SQL clients into intelligent assistants that improve productivity and reduce the learning curve for database interactions. -
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Keyv
Simple key-value storage with support for multiple backends
Keyv is a simple key-value storage system that supports multiple backends. It's designed to be a simple and consistent way to work with key-value stores. -
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Knex
A query builder for PostgreSQL, MySQL, CockroachDB, SQL Server, etc.
Knex.js is a flexible and portable SQL query builder for JavaScript. It supports multiple database systems, including PostgreSQL, MySQL, SQLite3, and more. Knex.js offers a powerful and intuitive API for building and executing SQL queries, making it a popular choice for Node.js applications requiring database interactions. -
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Koillection
Self-hosted service allowing users to manage collection
Koillection is a self-hosted web app for managing personal collections such as books, video games, electronics, and more. It allows users to track items, add metadata, upload images, and categorize collections by tags and types. Built with Symfony and Vue.js, Koillection is perfect for hobbyists and collectors seeking a customizable, private cataloging tool. -
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Kysely
A type-safe typescript SQL query builder
Kysely (pronounce “Key-Seh-Lee”) is a type-safe and autocompletion-friendly typescript SQL query builder. Inspired by knex. Mainly developed for node.js but also runs on deno and in the browser. Kysely makes sure you only refer to tables and columns that are visible to the part of the query you're writing. The result type only has the selected columns with correct types and aliases. As an added bonus you get autocompletion for all that stuff. As shown in the gif above, through the pure magic of modern typescript, Kysely is even able to parse the alias given to pet.name and add the pet_name column to the result row type. Kysely is able to infer column names, aliases and types from selected subqueries, joined subqueries, with statements and pretty much anything you can think of. Of course there are cases where things cannot be typed at compile time, and Kysely offers escape hatches for these situations. -
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Kysely SQL
A type-safe TypeScript SQL query builder
Kysely is a type-safe TypeScript SQL query builder that provides an intuitive and autocompletion-friendly API. It allows developers to construct complex SQL queries with full type safety, reducing runtime errors and improving code maintainability. Kysely supports various SQL dialects and is compatible with Node.js, Deno, and browser environments. -
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LINQ to DB
Linq to database provider
LINQ to DB is the fastest LINQ database access library offering a simple, light, fast, and type-safe layer between your POCO objects and your database. Architecturally it is one step above micro-ORMs like Dapper, Massive, or PetaPoco, in that you work with LINQ expressions, not with magic strings, while maintaining a thin abstraction layer between your code and the database. Your queries are checked by the C# compiler and allow for easy refactoring. However, it's not as heavy as LINQ to SQL or Entity Framework. There is no change-tracking, so you have to manage that yourself, but on the positive side you get more control and faster access to your data. In other words LINQ to DB is type-safe SQL. Alternatively, you can implement custom settings provider with ILinqToDBSettings interface. You can generate POCO classes from your database using T4 templates. -
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Laravel app
Add tags and taggable behaviour to your Laravel app
There are a lot of quality tagging packages out there. Most of them offer the same thing: creating tags, associating them with models and some functions to easily retrieve models with certain tags. But in our projects at Spatie we need more functionality. Last week we released our own - very opinionated - tagging package aptly called laravel-tags. It comes with batteries included. Out of the box it has support for translating tags, multiple tag types and sorting capabilities. After the package is installed (be sure to check the requirements first) the only thing you have to do is to add the HasTags trait to an Eloquent model to make it taggable. But we didn't stop with the regular tagging capabilities you find in every package. Laravel Tags comes with batteries included. Out of the box it has support for translating tags, multiple tag types and sorting capabilities. -
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Laravel-Translatable
A Laravel package for multilingual models
If you want to store translations of your models into the database, this package is for you. This is a Laravel package for translatable models. Its goal is to remove the complexity in retrieving and storing multilingual model instances. With this package you write less code, as the translations are being fetched/saved when you fetch/save your instance. If the property fallback is enabled in the configuration, then translatable will return the translation of the fallback locale for the fields where the translation is empty. This package is made to translate strings, but in general it's also able to translate numbers, bools or whatever you want to. Translatable is fully compatible with all kinds of Eloquent extensions, including Ardent. For tables already created in production, update your migrations to change the engine of the table before adding the foreign key constraint. -
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Laravel.io
The Laravel Community Portal
This is the repository for Laravel.io, the Laravel Community Portal where community members can share their Laravel knowledge, solve problems and build a solid community. Laravel.io features forums, articles, various community communication channels and more to keep you up to date on the latest Laravel developments and get you connected to like-minded Laravel users. It also has a thread search feature to easily find a relevant thread for your query, and you can also create a new thread. The code of this repository is completely open source, and offers optional Github authentication and Algolia search to run locally. -
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LiteStore
A lightweight, self-contained, RESTful, searchable, multi-format NoSQL
LiteStore is a lightweight static website CMS that uses SQLite as its backend. It enables users to create and manage simple content-driven websites without needing a complex CMS. LiteStore is designed for fast deployment, minimal setup, and efficient static page generation. -
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Mikro Orm
TypeScript ORM for Node.js based on Data Mapper, Unit of Work
TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. MikroORM allows handling transactions automatically. When you call em.flush(), all computed changes are wrapped inside a database transaction. Uses source code analysis so you do not have to repeat yourself when defining entities. Simply define correct TypeScript types and you are good to go! Supports MongoDB, MySQL, MariaDB, PostgreSQL and SQLite databases, and more can be supported via custom drivers right now. Keep your schema in sync with SchemaGenerator and Migrator. Supports both up and down migrations. With the Seeder and seeding factories, we can generate fake data of any volume/shape and seed the database with ease. Thanks to the UnitOfWork, all queries it fires are automatically batched. Inserts, updates, deletes - you name it! Powerful event system allows to hook into not only the entity lifecycle. Want to alter how the UnitOfWork works? Try onFlush event! -
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MongoDB Rust Driver
The official MongoDB Rust Driver
The MongoDB Rust Driver is a native, idiomatic Rust client for MongoDB that gives systems software and back-end services the ability to interact with MongoDB from safe, performant Rust code. It makes extensive use of Rust’s ownership and type systems to ensure memory safety, thread safety, and predictable performance without garbage collection overhead. The driver supports common MongoDB features like CRUD operations, indexing, aggregations, change streams, and transactions, enabling full use of the database’s capabilities from Rust applications. Because it’s asynchronous by design, it works well with Rust async runtimes like Tokio and async-std, letting developers build highly concurrent networked services that efficiently use modern multicore hardware. The crate also includes BSON encoding and decoding that maps cleanly to Rust types, so developers can work with rich document structures while retaining Rust’s performance guarantees. -
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MongoEngine
A Python Object-Document-Mapper for working with MongoDB
MongoEngine is a Python Object-Document Mapper for working with MongoDB. -
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Neon Database
Neon: Serverless Postgres. We separated storage and compute
The database you love, on a serverless platform designed to help you build reliable and scalable applications faster. Focus on building applications with time and money-saving features like instant provisioning, autoscaling according to load, and scale to zero. Instantly branch your data and schema to access isolated DB copies for development, CI/CD, and schema migrations with copy-on-write storage. Integrate it into your language or framework within minutes and unlock a simpler developer workflow. -
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Noisia
Harmful workload generator for PostgreSQL
noisia is a PostgreSQL workload generator designed for testing and benchmarking query performance. It simulates real-world SQL traffic by replaying or generating workloads based on defined query profiles. noisia is useful for stress testing databases, tuning configurations, and validating changes in performance-sensitive environments. -
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ODMantic
Sync and Async ODM (Object Document Mapper) for MongoDB
Odmantic is an Object-Document Mapper (ODM) for MongoDB, designed for Python applications using Pydantic models, providing a seamless integration with type safety and validation. -
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OpenViking
Context database designed specifically for AI Agents
OpenViking is an open-source context database engineered for efficient indexing and retrieval of large amounts of unstructured or semi-structured context data used by AI applications. It’s primarily designed to serve as a high-performance, scalable backend for storing app context, embeddings, conversational histories, and other textual artifacts that need rapid lookup and semantic search, which makes it especially useful for systems like chatbots or memory-augmented agents. The project is implemented with performance in mind, often leveraging optimized data structures that balance fast reads and writes with minimal resource consumption. Developers can integrate OpenViking into modern AI stacks to unify context storage across services, enabling consistent session history, personalized responses, and richer search experiences.
