Browse free open source Graph Databases and projects 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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  • 1
    ArcticDB

    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.
    Downloads: 35 This Week
    Last Update:
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  • 2
    sqlite-vec

    sqlite-vec

    A vector search SQLite extension that runs anywhere

    A vector search SQLite extension that runs anywhere.
    Downloads: 34 This Week
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  • 3
    Neovim DBee

    Neovim DBee

    Interactive database client for Neovim

    Interactive database client for Neovim. This project aims to be as cross-platform as possible, but there are some limitations (for example some of the go dependencies only work on certain platforms). To address this issue, the client implementations are detached from the main logic and they register themselves to DBee backend on plugin start. This allows the use of build constraints, which we use to exclude certain client implementations on certain platforms. You can pass an optional table parameter to the setup() function.
    Downloads: 29 This Week
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  • 4
    OWASP Amass

    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.
    Downloads: 27 This Week
    Last Update:
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    Nestjs boilerplate Microservice API

    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.
    Downloads: 17 This Week
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  • 6
    tigerbeetle

    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.
    Downloads: 16 This Week
    Last Update:
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  • 7
    AdminJS

    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.
    Downloads: 9 This Week
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  • 8
    pg_flo

    pg_flo

    Stream, transform, and route PostgreSQL data in real-time

    The easiest way to move and transform data between PostgreSQL databases.
    Downloads: 9 This Week
    Last Update:
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  • 9
    Laravel Migrations Generator

    Laravel Migrations Generator

    Generate your migrations from an existing database schema

    Automatically generate your migrations from an existing database schema. Generate Laravel Migrations from an existing database, including indexes and foreign keys. Laravel Migrations Generator will first generate all the tables, columns and indexes, and afterwards setup all the foreign key constraints. So make sure you include all the tables listed in the foreign keys so that they are present when the foreign keys are created.
    Downloads: 8 This Week
    Last Update:
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  • 10
    Backup Tables

    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.
    Downloads: 7 This Week
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  • 11
    Greenmask

    Greenmask

    PostgreSQL database anonymization and synthetic data generation tool

    Greenmask is a powerful open-source utility that is designed for logical database backup dumping, obfuscation, and restoration. It offers extensive functionality for backup, anonymization, and data masking. Greenmask is written in pure Go and includes ported PostgreSQL libraries that allows for platform independence. This tool is stateless and does not require any changes to your database schema. It is designed to be highly customizable and backward-compatible with existing PostgreSQL utilities. The Greenmask utility plays a central role in the Greenmask ecosystem. Our goal is to develop a comprehensive, UI-based solution for managing obfuscation procedures. We recognize the challenges of maintaining obfuscation consistency throughout the software lifecycle. Greenmask is dedicated to providing valuable tools and features that ensure the obfuscation process remains fresh, predictable, and transparent.
    Downloads: 7 This Week
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  • 12
    Testcontainers node

    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.
    Downloads: 7 This Week
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  • 13
    Valkey

    Valkey

    A flexible distributed key-value datastore

    Valkey is an open source (BSD) high-performance key/value datastore that supports a variety of workloads such as caching, and message queues, and can act as a primary database. Valkey can run as either a standalone daemon or in a cluster, with options for replication and high availability. Valkey natively supports a rich collection of datatypes, including strings, numbers, hashes, lists, sets, sorted sets, bitmaps, hyperloglogs, and more. You can operate on data structures in-place with an expressive collection of commands. Valkey also supports native extensibility with built-in scripting support for Lua and supports module plugins to create new commands, data types, and more.
    Downloads: 7 This Week
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  • 14
    Cayley

    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.
    Downloads: 6 This Week
    Last Update:
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  • 15
    mongo-express

    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.
    Downloads: 6 This Week
    Last Update:
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  • 16
    Spring Data Neo4j

    Spring Data Neo4j

    Provide support to increase developer productivity in Java

    Spring Data Neo4j, part of the larger Spring Data family, provides easy configuration and access to Neo4j Graph Databases from Spring applications. It offers three different levels of abstraction to access the store. The Neo4j client, the Neo4j Template, and the Neo4j Repositories. Spring Data Neo4j offers advanced features to map annotated entity classes to the Neo4j Graph Database. The template programming model is equivalent to other Spring templates and builds the basis for interaction with the graph and is also used for the Spring Data repository support. Spring Data Neo4j is a core part of the Spring Data project which aims to provide convenient data access for NoSQL databases. Spring Data builds on Spring Framework, check the spring.io web-site for a wealth of reference documentation. If you are just starting out with Spring, try one of the guides.
    Downloads: 4 This Week
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  • 17
    EdgeDB

    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.
    Downloads: 3 This Week
    Last Update:
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  • 18
    Bytebase

    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.
    Downloads: 2 This Week
    Last Update:
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  • 19
    Dokploy

    Dokploy

    Open Source Alternative to Vercel, Netlify and Heroku

    Streamline your operations with our all-in-one platform, perfect for managing projects, data, and system health with simplicity and efficiency. Simplify your project and data management, ensure robust monitoring, and secure your backups—all without the fuss over minute details. Elevate your infrastructure with tools that offer precise control, detailed monitoring, and enhanced security, ensuring seamless management and robust performance. Streamline your deployments with our PaaS. Effortlessly manage Docker containers and traffic with Traefik. Boost your infrastructure's efficiency and security today
    Downloads: 2 This Week
    Last Update:
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  • 20
    GUN

    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.
    Downloads: 1 This Week
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  • 21
    Laravel Options

    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.
    Downloads: 1 This Week
    Last Update:
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  • 22
    PyMongo

    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.
    Downloads: 1 This Week
    Last Update:
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  • 23
    SurrealDB

    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.
    Downloads: 1 This Week
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  • 24
    adminMongo

    adminMongo

    adminMongo is a Web based user interface (GUI) to handle MongoDB

    adminMongo is a cross-platform user interface (GUI) to handle all your MongoDB connections/database needs. adminMongo is fully responsive and should work on a range of devices. adminMongo can also be used as a cross-platform Electron application. Due to the size of Electron it will need to be built manually.
    Downloads: 1 This Week
    Last Update:
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  • 25
    Blazegraph (powered by bigdata)

    Blazegraph (powered by bigdata)

    Fast, scalable, robust graph database platform

    Blazegraph has moved to Github. Please see https://github.com/blazegraph/database/.
    Downloads: 5 This Week
    Last Update:
    See Project
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Open Source Graph Databases Guide

Open source graph databases are a powerful type of data storage system that allow users to store and manage information in an organized and efficient manner. Graph databases make use of the network-like structure known as “graphs”, that allow for linkages between data points that are easy to visualize. This makes them particularly useful for representing complex relationships between disparate objects or data points.

Unlike traditional relational database management systems where the primary form of interaction is through SQL queries, open source graph databases offer multiple ways to interact with the stored information using standard query languages like Gremlin or SPARQL. Additionally, they also provide greater scalability than other types of databases, allowing organizations to more easily build large knowledge graphs as their needs grow and develop over time. Additionally, because these systems are open source, users have full flexibility in terms of customizing them according to their own specific requirements and preferences.

Finally, one of the major benefits of open source graph databases is that they enable developers to create applications quickly due to increased flexibility when designing software solutions–they allow developers to rapidly prototype and test ideas without having to worry about compatibility with existing structures or interfaces within a framework. Furthermore many such systems also come pre-packaged with additional tools like analytics dashboards which give users more detailed insights into how their data is being used.

Features Provided by Open Source Graph Databases

  • Query language: Many open source graph databases provide support for querying data using specialized query languages. For example, Cypher is a popular query language used to retrieve and manipulate data stored in Neo4j.
  • Index-free adjacency: Open source graph databases employ index-free adjacency, meaning relationships between nodes are stored with the nodes themselves rather than in an external index. This allows for faster reads during traversals of highly connected datasets than when using more traditional search algorithms.
  • Labeled property graphs: Label property graphs enable users to store arbitrary key value pairs on nodes and edges providing a flexible schema that can be changed at any time without having to rebuild the entire database structure.
  • Scalability: Scalability is an important feature provided by some open source graph databases as it ensures that the dataset can grow or shrink as needed while maintaining performance consistency.
  • Fault tolerance: Some open source graph databases provide fault tolerant features such as replication which allow for data sets to remain available even when part of the system fails or goes down for maintenance.
  • High Availability: High availability enables a distributed cluster of machines to keep running in case part of them fail or need replacing, reducing downtime and improving reliability

Types of Open Source Graph Databases

  • Native Graph Databases: Native graph databases represent relationships as edges and vertices within the database itself without having to model them. This allows for quick traversal of connected data, making it ideal for real-time applications such as recommendation engines or social networks.
  • Object-Graph Mapping (OGM): OGM is a type of abstraction layer between an object-oriented programming language and a graph database. This provides developers with a consistent way to store objects in the graph database, allowing them to interact with the data using their preferred language without having to learn complex query languages such as Gremlin or Cypher.
  • Property Graph Databases: Property graph databases are similar to native graph databases but provide additional functions such as labels, properties and constraints on nodes and edges. These elements allow additional insights into patterns among connected data, making property graphs well suited for analytics applications.
  • RDF Triple Stores: RDF Triple stores are a type of NoSQL datastore that store information as Resource Description Framework (RDF) triples consisting of subject, predicate and object fields forming statements about resources described by URIs or blank nodes. As each triple defines an explicit relationship between two resources, it can be used to form abstractions over large datasets rapidly for use in semantic web applications.

Advantages of Using Open Source Graph Databases

  1. Increased Flexibility: Open source graph databases offer increased flexibility, giving developers the ability to develop and customize applications without having to rely on vendor-provided software. It allows developers to customize their data models and optimize queries without being restricted by a vendor’s pre-defined design.
  2. High Performance: Open source graph databases provide high performance for both large and small datasets due to their optimized querying capabilities. The use of indexing techniques and caching strategies allow for faster access times, which can make all the difference when working with larger datasets.
  3. Cost Efficiency: Using open source graph databases is much more cost efficient than purchasing expensive database programs from vendors. This allows organizations that have limited budgets to still benefit from the power of graph databases without having to shell out a lot of cash upfront.
  4. Scalability: Open source graph databases are designed for scalability so they can be easily scaled up or down depending on the needs of an organization as it grows. This makes them ideal if you plan on handling increasingly large data sets over time as businesses need more sophisticated solutions that can handle larger volumes of data quickly and accurately.
  5. Easy Integration: Open source graph databases are designed with integration in mind, allowing users to integrate their existing systems with new components seamlessly. This makes it easier to implement new features while still keeping the existing codebase intact, saving time and money in development projects that require multiple components working together harmoniously.

Who Uses Open Source Graph Databases?

  • Developers: Developers are individuals who use open source graph databases to create custom software, websites, and other digital applications. They leverage the capabilities of these databases in order to meet their unique project requirements.
  • Researchers: Researchers utilize open source graph databases to analyze large data sets and uncover meaningful patterns or trends. They are able to draw insights that would not be possible with traditional relational databases.
  • Businesses: Companies use open source graph databases for a variety of purposes such as customer segmentation, fraud detection, recommendation systems, and more. This type of database allows businesses to gain valuable insights about their customers that can be used for targeted marketing and customer engagement initiatives.
  • Academic Institutions: Educational institutions often take advantage of open source graph databases for research projects. By using this type of database, students and faculty alike can access large datasets quickly and accurately in order to uncover new knowledge or solutions that may not have been previously available without them.
  • Government Agencies & Nonprofits: Government agencies and nonprofit organizations may use open source graph databases when performing analysis on large datasets in order to identify potential savings opportunities or discover areas where additional funding could be allocated strategically.

How Much Do Open Source Graph Databases Cost?

Open source graph databases are typically free, making them attractive to many businesses. However, there may be costs associated with setting up, maintaining, and running the database. Depending on the complexity of your project, you could incur fees for developing custom software or a high-performance server system. You may also need to purchase a license for some proprietary software that is used in conjunction with the open source graph databases. Additionally, you may choose to hire a consultant or pay for services like training and support. In addition to these costs, it’s important to factor in the cost of your time spent researching and learning how to use the database correctly as well as any other out-of-pocket expenses related to setting up and running the database. Ultimately, when compared to other database options out there such as private cloud solutions or even traditional relational databases, open source graph databases can provide an economical solution that is accessible and scalable enough for most projects.

What Software Can Integrate With Open Source Graph Databases?

Open source graph databases can integrate with a variety of software types, including customer relationship management (CRM) systems, enterprise resource planning (ERP) systems, artificial intelligence (AI) applications, and analytics platforms. Each of these software types has its own strengths when integrated with an open source graph database. For example, CRM systems make it easier to manage customer data by allowing organizations to track customer demographics and interactions. ERP systems facilitate the efficient use of resources by automating time-consuming administrative tasks such as inventory tracking and financial forecasting. AI applications can provide additional insights from large datasets stored in the graph database by detecting patterns which are otherwise undetectable by humans. Analytics platforms give users greater insight into their data by providing streamlined visualizations for current trends or anomalies in the data. By integrating any one of these software types with an open source graph database, a company is able to leverage their existing resources more effectively while gaining valuable new insights into their data that will help them improve their operations and stay ahead of the competition.

Trends Related to Open Source Graph Databases

  1. Increased Popularity: Open source graph databases have become increasingly popular, as they provide a cost-effective and easy to use solution for storing and querying graph data. They are also often used in combination with other software, such as machine learning and artificial intelligence applications.
  2. Improved Performance: Open source graph databases offer improved performance compared to relational databases. They are highly scalable and can handle large amounts of data easily. Furthermore, they can be installed quickly and do not require a complex set up process.
  3. Improved Data Modeling: Graph databases offer an efficient way of modeling data that is based on relationships between entities. This makes it easier to store, query and analyze data.
  4. Expanded Use Cases: Open source graph databases are being used for a wide range of applications, from social networks to financial systems and from recommendation engines to fraud detection systems. They provide an efficient way of dealing with complex queries and can be used to gain insights from large datasets.
  5. Easier Integration: Open source graph databases can be easily integrated into existing applications, as they provide APIs that can be used to access the database. Moreover, they can also be integrated with other software solutions such as machine learning libraries, analytics platforms and visualization tools.
  6. Enhanced Security: Open source graph databases offer enhanced security features such as authentication, authorization, encryption, data masking and audit trails. This makes them suitable for applications where security is a priority.

How To Get Started With Open Source Graph Databases

First, you will need to decide which specific open source graph database you want to use. Popular options include Neo4j, JanusGraph, OrientDB and ArangoDB. Each of these different databases have unique features that can fulfill your needs; do some research on each as well as read reviews to determine the best fit for your project.

Once you've selected the right database for your requirements, download it from the internet - most open source graph databases are freely available online. Installation instructions should be provided with any downloads; follow those closely and make sure to pay attention to any special prerequisites or compatibility requirements prior to installation.

When you have successfully installed your chosen graph database, you'll need to create a schema - this is basically an outline of what data elements will be stored in the database and how they are related. It's also important at this stage that all necessary permissions are granted, such as who has access rights etc., as well as ensuring that backups/recovery plans are ready if needed. Most modern graph databases feature user-friendly entry points for setting up schemas such as graphical editors or interactive command lines - consult the documentation of your selected product for details on how best to set up yours accordingly.

With everything installed and configured properly, you should now be ready to start using your open source graph database. Your next step should likely be loading some data into it so that it can start performing useful queries or analytics tasks - go through the product’s documentation again so that you understand how data can be added and updated within the system. Finally - start playing around. Writing code against various APIs may sound intimidating but don't worry: there's lots of readily available sample code out there aimed at helping developers get quickly familiarized with their chosen technology stack including graph databases like Neo4J etc.

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