Open Source Windows Graph Databases
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Graph Databases for Windows
View 20 business solutionsBrowse free open source Graph Databases and projects for Windows below. Use the toggles on the left to filter open source Graph Databases by OS, license, language, programming language, and project status.
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OWASP Amass
In-depth attack surface mapping and asset discovery
The OWASP Amass Project has developed a tool to help information security professionals perform network mapping of attack surfaces and perform external asset discovery using open source information gathering and active reconnaissance techniques. The Open Web Application Security Project (OWASP) is a nonprofit foundation that works to improve the security of software. All of our projects ,tools, documents, forums, and chapters are free and open to anyone interested in improving application security. The volume argument allows the Amass graph database to persist between executions and output files to be accessed on the host system. The first field (left of the colon) of the volume option is the amass output directory that is external to Docker, while the second field is the path, internal to Docker, where amass will write the output files. -
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ArcticDB
ArcticDB is a high performance, serverless DataFrame database
Built for the modern Python Data Science ecosystem, ArcticDB transforms your ability to handle complex real-world data with an Incredibly fast proven Petabyte scale. ArcticDB is designed with quant users in mind. It allows you to self-manage your data leveraging your preferred infrastructure. Giving you the keys to protect your most valuable asset. Supports large concurrent writes to many tables ensuring datasets can be onboarded fast and in the most convenient format. Scale-out architecture and built-in compression ensure that networks and storage are utilized efficiently. Support for DataFrames with thousands of columns enables large trading universes. -
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sqlite-vec
A vector search SQLite extension that runs anywhere
A vector search SQLite extension that runs anywhere. -
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tigerbeetle
The financial transactions database designed for mission critical safe
TigerBeetle is production-ready on Linux and seamlessly integrated with major programming languages. TigerBeetle is a financial transactions database designed for mission-critical safety and performance to power the next 30 years of OLTP. TigerBeetle redesigns the distributed database storage engine and consensus protocol for the OLTP workload. This solves the problem of OLTP write contention to unlock three orders of magnitude more performance than a general purpose (OLGP) database. The language of business transactions around the world is Debit/Credit. TigerBeetle ships with this schema out of the box. A single TigerBeetle cluster can process over 100 billion transactions, at a hundredth of the cost compared to legacy, proprietary, or cloud databases. -
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AdminJS
AdminJS is an admin panel for apps written in node.js
Our system leverages AI to effortlessly generate text. Simplify your product database management with just one click. The out-of-the-box version of AdminJS is pretty powerful, but its in-depth customizability is where it really shines. With a basic knowledge of React and Node.js, you can change nearly every behavior of your admin panel. With AdminJS you can Create, Read, Update, and Delete all of your resources, no matter where they come from. Thanks to the tight integration with your ORM/ODM, AdminJS picks up all the validation rules, data types, and relationships. AdminJS has a simple interface for connecting multiple data sources like SQL/noSQL databases and multiple APIs. We already created adapters for the most popular services. With AdminJS, you can easily find any record inside your dataset. Everything thanks to the advanced filters panel which is able to narrow your search according to multiple criteria. -
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Bytebase
The GitHub/GitLab for database DevSecOps
The GitHub/GitLab for database DevSecOps. World's most advanced database DevSecOps solution for Developer, Security, DBA and Platform Engineering teams. -
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PyMongo
PyMongo - the Official MongoDB Python driver
The PyMongo distribution contains tools for interacting with MongoDB database from Python. The bson package is an implementation of the BSON format for Python. The pymongo package is a native Python driver for MongoDB. The gridfs package is a gridfs implementation on top of pymongo. -
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SurrealDB
A scalable, distributed, collaborative, document-graph database
With an SQL-style query language, real-time queries with highly-efficient related data retrieval, advanced security permissions for multi-tenant access, and support for performant analytical workloads, SurrealDB is the next generation serverless database. SurrealDB is the ultimate cloud database for tomorrow's applications. SurrealDB is an innovative NewSQL cloud database, suitable for serverless applications, jamstack applications, single-page applications, and traditional applications. It is unmatched in its versatility and financial value, with the ability for deployment on cloud, on-premise, embedded, and edge computing environments. For a hassle-free setup, get started with SurrealDB Cloud in one-click. There is no need for your team to learn new complicated database languages. Getting started with SurrealDB is as simple as one command - and advanced functionality is simple to understand, whilst still being fast and performant. -
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Blazegraph (powered by bigdata)
Fast, scalable, robust graph database platform
Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/. -
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Resources
Relative Examples and Resources, etc...
IOs, Graph Database Wrapper and more examples for iBoxDB Download Mirrors https://sourceforge.net/settings/mirror_choices?projectname=application-database&filename=iboxdb392.zip&selected=pilotfiber -
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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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Nestjs boilerplate Microservice API
Nestjs boilerplate microservice api
A boilerplate for building microservices with NestJS, this provides a template with essential components for microservice architecture. -
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Testcontainers node
Supports tests, providing lightweight, throwaway instances of database
Testcontainers is an open source library for providing throwaway, lightweight instances of databases, message brokers, web browsers, or just about anything that can run in a Docker container. No more need for mocks or complicated environment configurations. Define your test dependencies as code, then simply run your tests and containers will be created and then deleted. With support for many languages and testing frameworks, all you need is Docker. Use a containerized instance of your database to test your data access layer code for complete compatibility, without requiring a complex setup on developer machines. Trust that your tests will always start with a known state. Use containerized web browsers, compatible with Selenium, to run automated UI tests. Each test gets a fresh, clean instance of the browser, without having to worry about variations in plugins or required updates. -
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mongo-express
Web-based MongoDB admin interface, written with Node.js
A web-based MongoDB admin interface written with Node.js, Express, and Bootstrap 5. -
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ChartDB-Desktop
ChartDB Desktop Version
Download ChartDB for desktop | Descarga ChartDB para escritorio This project is an opensource fork of ChartDB, adapted to desktop. It contains ChartDB functionalities but no AI integration. For this, the Electron library was used. Este proyecto es un fork opensource de ChartDB, adaptado al escritorio. Contiene las funcionalidades de ChartDB pero sin integración AI. Para ello, se utilizó la biblioteca Electron. -
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TRAK Viewpoints
Specifications for TRAK architecture views
The architecture viewpoints (specifications for architecture views iaw ISO 42010) for TRAK. TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Defines a total of 24 viewpoints. The ones needed are selected by taking the task sponsor's concerns and matching them to the typical concerns that each TRAK viewpoint addresses. The triples that address each concern are defined in the TRAK metamodel (https://sf.net/p/trakmetamodel). The mapping between metamodel triple and architecture viewpoint is held with a Neo4J graph model (https://doi.org/10.1002/eng2.12168) and defined using (more) architecture viewpoints (https://www.researchgate.net/publication/335176248_Architecture_Description_Viewpoints_Metamodel_Description_Implementation_and_Model_Changes). The minimal process is defined in the overall TRAK specification (https://sf.net/p/trak) -
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TRAK Metamodel
Tuples (triples) for TRAK architecture viewpoints and views
The definition of the metamodel for TRAK (defines allowed AD elements and relationships i.e. tuples/ triples for the TRAK viewpoints and views). TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Forms basis for RDF + OWL ontology description - see https://trakmetamodel.sourceforge.io/vocab/TRAK_metamodel.html. Each TRAK metamodel element now has its own web page - see https://trakmetamodel.sourceforge.io/metamodel/index.html -
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**Zastosowanie**: Głównym celem projektu jest optymalizacja wykorzystania pamięci w graficznych bazach danych poprzez analizę podobieństwa cosinusowego wektorów cech obrazów. Umożliwia identyfikację duplikatów (obrazów bardzo do siebie podobnych), co prowadzi do efektywniejszego zarządzania zasobami. **Program** W chwili obecnej program przeszukuje obrazy w katalogu, do którego ścieżka została zapisana w pliku 'Data\settings.txt'. **Użycie**: Program obsługuje się w terminalu. Po piewszym wykonaniu programu, zostaje utworzony katalog Data, w miejscu gdzie zapisany jest program. Aby wybrać ścieżkę do katalogu z obrazami należy w pliku 'settings.txt' zapisać ścieżkę. Następnie można wykonywać program z: -an, -mnb, -c, -i Link do GitHub: https://github.com/Duke-Axer/Duplicate-Finder Wszystkie pytania proszę pisać na b.gabka.nkn@gmail.com
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Backup Tables
Backup single or multiple database tables with ease
Backup single or multiple database tables with ease. Use the BackupTables::generateBackup($tableToBackup) Facade anywhere in your application and it will generate $tableToBackup_backup_2024_08_22_17_40_01 table in the database with all the data and structure. Note that the datetime 2024_08_22_17_40_01 will be varied based on your datetime. -
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BadgerDB
Fast key-value DB in Go
BadgerDB is an embeddable, persistent and fast key-value (KV) database written in pure Go. It is the underlying database for Dgraph, a fast, distributed graph database. It's meant to be a performant alternative to non-Go-based key-value stores like RocksDB. Badger is stable and is being used to serve data sets worth hundreds of terabytes. Badger supports concurrent ACID transactions with serializable snapshot isolation (SSI) guarantees. A Jepsen-style bank test runs nightly for 8h, with --race flag and ensures the maintenance of transactional guarantees. Badger has also been tested to work with filesystem-level anomalies, to ensure persistence and consistency. Badger is being used by a number of projects including Dgraph, Jaeger Tracing, UsenetExpress, and many more. BadgerDB is a pretty special package from the point of view that the most important change we can make to it is not on its API but rather on how data is stored on disk. -
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Cayley
An open-source graph database
Cayley is a free and open source database for Linked Data. Inspired by the graph database behind Google's Knowledge Graph (formerly Freebase), it offers a similar experience for Freebase fans and more. Cayley has a built-in query editor, visualizer and REPL, as well as support for multiple Query languages, including Gizmo (Gremlin dialect), MQL and GraphQL dialect. Cayley is also highly modular, so you can easily extend and connect it to your favorite programming languages and back-end stores. Cayley works on top of your existing database no matter the data model. It’s been well tested by numerous companies for their production workloads and is therefore very production-ready. -
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Common Resource Grep - crgrep
Common Resource Grep
CRGREP searches for matching text in databases, various document formats, archives and other difficult to access resources. A command line tool for name and content text matching in database tables, plain files, MS Office documents, PDF, archives, MP3 audio, image meta-data, scanned documents, maven dependencies and web resources. CRGREP will search resources within resources of any arbitrary combination or depth, so text within a document within a zip archive, and so on. Here you will find binary downloads and discussion (https://sourceforge.net/p/crgrep/discussion/) . The actual development and issue tracking can be found here: https://bitbucket.org/cryanfuse/crgrep -
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Cosmos DB Spark
Apache Spark Connector for Azure Cosmos DB
Azure Cosmos DB Spark is the official connector for Azure CosmosDB and Apache Spark. The connector allows you to easily read to and write from Azure Cosmos DB via Apache Spark DataFrames in Python and Scala. It also allows you to easily create a lambda architecture for batch-processing, stream-processing, and a serving layer while being globally replicated and minimizing the latency involved in working with big data. -
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Crase enables instant access to structured information (personal contacts, software modelling, ..., whatever). The functionality is based on the mix of techniques, such as the graph database, metadata and functionality from composition and others.
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Dokploy
Open Source Alternative to Vercel, Netlify and Heroku
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