Top 10 Graph Databases to Watch Out for in 2021

Are you looking for a database that can handle complex relationships and interconnected data? Look no further than graph databases! Graph databases are designed to store and manage data in a way that reflects the relationships between entities. They are perfect for applications that require complex queries and data analysis.

In this article, we will introduce you to the top 10 graph databases to watch out for in 2021. These databases are chosen based on their popularity, features, and community support. Let's dive in!

1. Neo4j

Neo4j is the most popular graph database in the market. It is a fully ACID-compliant database that supports both open-source and enterprise versions. Neo4j has a rich set of features, including a powerful query language (Cypher), high scalability, and a robust security model. It is widely used in various industries, including finance, healthcare, and social media.

2. Amazon Neptune

Amazon Neptune is a fully managed graph database service that is built for the cloud. It is highly available, scalable, and secure. Amazon Neptune supports both open-source and proprietary graph database engines, including Apache TinkerPop and Gremlin. It is a great choice for applications that require high performance and low latency.

3. JanusGraph

JanusGraph is an open-source, distributed graph database that is built on top of Apache Cassandra and Apache HBase. It is designed to handle large-scale graphs with billions of vertices and edges. JanusGraph supports various graph query languages, including Gremlin and SPARQL. It is widely used in various industries, including finance, healthcare, and social media.

4. ArangoDB

ArangoDB is a multi-model database that supports graph, document, and key-value data models. It is a fully ACID-compliant database that is highly scalable and secure. ArangoDB supports various query languages, including AQL, Gremlin, and SPARQL. It is widely used in various industries, including finance, healthcare, and social media.

5. OrientDB

OrientDB is a multi-model database that supports graph, document, and key-value data models. It is a fully ACID-compliant database that is highly scalable and secure. OrientDB supports various query languages, including SQL, Gremlin, and SPARQL. It is widely used in various industries, including finance, healthcare, and social media.

6. TigerGraph

TigerGraph is a distributed graph database that is designed for real-time analytics. It is highly scalable and supports various query languages, including GSQL and SQL. TigerGraph is widely used in various industries, including finance, healthcare, and social media.

7. Stardog

Stardog is a graph database that is designed for enterprise applications. It is a fully ACID-compliant database that supports various query languages, including SPARQL and SQL. Stardog is widely used in various industries, including finance, healthcare, and social media.

8. Dgraph

Dgraph is an open-source, distributed graph database that is designed for real-time applications. It is highly scalable and supports various query languages, including GraphQL and DQL. Dgraph is widely used in various industries, including finance, healthcare, and social media.

9. Virtuoso

Virtuoso is a graph database that is designed for enterprise applications. It is a fully ACID-compliant database that supports various query languages, including SPARQL and SQL. Virtuoso is widely used in various industries, including finance, healthcare, and social media.

10. AllegroGraph

AllegroGraph is a graph database that is designed for enterprise applications. It is a fully ACID-compliant database that supports various query languages, including SPARQL and Prolog. AllegroGraph is widely used in various industries, including finance, healthcare, and social media.

Conclusion

Graph databases are becoming increasingly popular due to their ability to handle complex relationships and interconnected data. In this article, we introduced you to the top 10 graph databases to watch out for in 2021. These databases are chosen based on their popularity, features, and community support. Whether you are building a social network, a recommendation engine, or a fraud detection system, these graph databases will help you manage your data efficiently and effectively.

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