Open Source Graph Databases - Page 2
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Inventory and Order Management Software for Multichannel SellersWe are the most powerful inventory and order management platform for Amazon, Walmart, and multichannel product sellers. Centralize orders, product information, and fulfillment operations to run more efficiently, sell more products, and stay compliant with marketplace requirements so you can grow profitably.
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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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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Resources
Relative Examples and Resources of iBoxDB, etc...
IOs, Graph Database Wrapper and more examples for iBoxDB Download Mirrors https://sourceforge.net/settings/mirror_choices?projectname=application-database&filename=iboxdb411.zip&selected=pilotfiber -
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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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Blazegraph (powered by bigdata)
Fast, scalable, robust graph database platform
Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/. -
Data management solutions for confident marketingVerify, deduplicate, manipulate, and assign records automatically to keep your CRM data accurate, complete, and ready for business.
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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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Graph Database
A robust, reliable, user-friendly, and high-performance Graph Database
This is an academic project to build a graph database, supporting multiple users, with fully functioned data query, data manipulation and indexing mechanism. It is running in a distributed client-server mode. This project is assigned to final-year project from group IT121B, Bachelor of Computing, University of Wollongong. -
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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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reco4j-neo4j
Reco4j is a graph-based recommendation engine, this is the neo4j impl
Reco4j is an open source project aims at developing a recommendation framework based on graph data sources. We choose graph databases for several reasons. They are NoSQL databases, so "schemaless". This means that it is possible to extend the basic data structure with intermediate information, i.e. similarity value between item and so on. Moreover, since every information is expressed with properties, nodes and relations, the recommendation process can be customized to work on every graph. Reco4j can be used on every graph where "user" and "item" is represented by node and the preferences are modelled as relationship between them. Current implementation leverage on Neo4j as first graph database integrated in our framework. -
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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. -
Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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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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CrispI
A hybrid graph database with analysis
A graph database layer in Java which allows mixed-mode database handling. For example, using an underlying oodb, a OneToMany and ManyToOne relationships can be implemented allowing quick and robust hierarchies to be built (a subset of a graph). The system also includes a Big Data implementation, other analytics and visualization. The current invokation is based on a Versant Db. Examples for use can be found in CrispI-Examples. -
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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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EdgeDB
A next-generation graph-relational database
The world's favorite graph-relational database is back for an action-packed sequel. Tune in for a series of lightning talks breaking down what's new and what's next for EdgeDB. EdgeDB is an open-source database designed as a spiritual successor to SQL and the relational paradigm. It aims to solve some hard design problems that make existing databases unnecessarily onerous to use. Powered by the Postgres query engine under the hood, EdgeDB thinks about schema the same way you do: as objects with properties connected by links. It's like a relational database with an object-oriented data model, or a graph database with strict schema. We call it a graph-relational database. The core unit of schema in the graph-relational model is the object type, analogous to a table in SQL. Object types contain properties and can be linked to other object types to form a schema graph. -
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GUN
Cybersecurity protocol for syncing decentralized graph data
GUN is a small, easy, and fast data sync and storage system that runs everywhere JavaScript does. The aim of GUN is to let you focus on the data that needs to be stored, loaded, and shared in your app without worrying about servers, network calls, databases, or tracking offline changes or concurrency conflicts. This lets you build cool apps fast. When a browser peer asks for data, it'll merge the reply with its own data using a CRDT, then cache the result. GUN is fully decentralized (peer-to-peer or multi-master), meaning that changes are not controlled by a centralized server. A server can be just another peer in the network, one that may have more reliable resources than a browser. You save data on one machine, and it will sync it to other peers without needing a complex consensus protocol. It just works. GUN can be used in both browsers and servers. We have made it easy to install in many different environments. -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks. It is recommended to explore them. All of the commands and features supported by graph notebook are explained in detail with examples within the sample notebooks. You can find them here. As this project has evolved, many new features have been added. If you are already familiar with graph-notebook but want a quick summary of new features added, a good place to start is the Air-Routes notebooks in the 02-Visualization folder. -
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Graph Portal
Software to build web portals using concepts of Graph Theory
Graph Portal allows to organize many types of data so that you can get the information you want in the easiest way possible. There are many use cases for this software, including: building a web portal, creating mind map, wiki, studying graph theory concepts and algorithms,content management etc. The application has built-in Lucene search, custom query, file attachment to nodes etc. Graph Portal comes with an optional built-in security for authentication and role-based authorization. There are multiple levels of customization (depending on the technical skills of the customer) for branding the implementation to customer needs. The software exposes RESTFul services for integration with third-party user interfaces. This is a web based software and can be accessed from computers, tablets and phones from anywhere. -
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Grinn
graph database and R package for omic data integration
http://kwanjeeraw.github.io/grinn/ -
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IP database REST API
Open Source REST API for IP database, includes qqwry/ipipdotnet
Open Source REST API for IP database, includes qqwry, ipipdotnet. -
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Laravel Options
Global key-value store in the database
Global key-value store in the database. To get started with options, use Composer to add the package to your project's dependencies. Run PHP artisan migrate to migrate the table. There will now be an options table in your database. -
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Nebula Graph
A distributed, fast open-source graph database
The graph database built for super large-scale graphs with milliseconds of latency. Optimized SUBGRAPH and FIND PATH for better performance. Optimized query paths to reduce redundant paths and time complexity. Optimized the method to get properties for better performance of MATCH statements. Nebula Graph adopts the Apache 2.0 license, one of the most permissive free software licenses in the world. Free as in freedom, because, under the Apache 2.0 license, you can use, copy, modify and redistribute Nebula Graph, even for commercial purposes, all without asking for permission. We believe that great open source projects are not built in isolation, but rather by a community of contributors. We welcome contributions to Nebula Graph from anyone regardless of skill level or background in software development. If you have an idea for a feature you would like to see added, or you have identified a bug that needs fixing, please don't hesitate to submit an issue to our Github repository. -
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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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STON
Translator of SBGN PD and AF maps into Neo4j graph database.
STON, Sbgn TO Neo4j, is a Java-based framework that imports and translates metabolic, signalling and gene regulatory pathways presented in SBGN (Systems Biology Graphical Notation, http://www.sbgn.org) Process Description (PD) and Activity Flow (AF) languages to a graph-oriented format compatible with Neo4j (http://neo4j.com/). STON1.2 allows also to link common processes between two different PD maps. This framework uses two sets of libraries: LibSBGN and Neo4j libraries. Requirements: Java 1.8 is necessary. Works with Neo4j Community Edition 2.3.1 -
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SGDB is an embedded graph database written in JAVA. Goal of SGDB is to provide decent performance for breadth traversal processing even for larger graphs.
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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
