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The world’s leading graph databases

The increase in data has led to a growing need for graph databases or technologies.  With a graph database, the relationships that exist within the data can be stored, refined and queried properly. A graph database, therefore, is a database created to store data without restricting it to a pre-set model. The data in these graph-based technology expresses how each entity is related to others.

Nodes and edges are quite important when looking at graph databases as the later represents the relationship with the former. This nodes and edges setup, makes the retrieval and querying of relationships easier. Retrieving complex hierarchical structures is an advantage that these graph technologies have over relational databases. The software review forum G2 has a list of the top-rated graph databases in the market. The leading graph database technologies on G2 have had more reviews, a higher percentage of positive feedback, more data generated from other online networks and social platforms.

Most notable graph databases

ArangoDB: ArangoDB is currently rated 4.8 out of 5 from 44 reviews on G2. It is a free and open source native multimodal database. Combining a Resource Description Framework (RDF) and a graph database. ArangoDB supports three data models with one database core and a consolidated query language. The ArangoDB Query Language (AQL) can be compared to the Structured Query Language (SQL). The key difference is that AQL is not capable of defining operations. These operations consist of the creating and dropping of databases, indexes and collections. Some of the positive product reviews reveal its impressive feature-rich query language (AQL) and its ease of use compared to other graph-based query languages. Other notable advantages are the complete admin UI and the presence of graph traversal algorithms. 

Neo4j: A leading native graph database and graph platform that is used by companies such as Adobe, eBay, Lyft, Comcast and a host of others. It is currently rated number two on G2 with an average of 4.5 out of 5 from 39 reviews. As a graph database, it is available via open source and also has a commercial licence. There is an enterprise-level of security, performance and reliability with this product. Neo4j is believed to have successfully implemented a property graph model to the storage level. 

Source: Neo4j

The example above from Neo4j highlights the inclusion of properties in the graph model. Interestingly, the properties are established at both the node and edge level. With the example above, Amy Peters as an employee or a node has properties such as name, date of birth and employee ID. While the edge HAS_CEO has a property known as start_date. Cypher is the query language of Neo4j and works across Apache Spark, Neo4j and Gremlin-based products. They also have other useful products such as Neo4j Bloom, Neo4j ETL and Neo4j Aura. They’ve also created an Ebook which is a great introduction to the world of graph databases. 

OrientDB: OrientDB is viewed as a database designed for the modern world. It tags itself as the fastest graph database and first multimodal database. It is currently third based on G2’s graph database ranking. With a score of 4.0 out of 5 from 37 reviews. Some of the reviewers rate the graph database high based on the ease in usability and the fast and smooth process of converting SQL to a graph. It is also considered to be swift in processing queries and efficient in the retrieval of data. OrientDB empowers organisations to tap into the capabilities of graph databases without having to roll out multiple applications.  An approach that enhances security, performance and scalability. 

Amazon Neptune: In 2017, Amazon launched a graph database platform called Neptune. A technology that has been specifically designed for relationship graphs. It is no surprise that this product has been enhanced to withstand billions of relationships and run queries within milliseconds. As a graph database, it is believed to be compatible with Property Graph and W3C’s RDF and their respective query languages Apache TinkerPop Gremlin and SPARQL. Some of the use cases for Amazon Neptune include recommendation engines, drug discovery, network security, knowledge graphs and fraud detection. As a graph-based technology, it has a continuous backup to Amazon S3 and has secure support for HTTPS encrypted client connections.  Amazon Neptune is currently rated 4.0 out of 5.0 from a total of 13 reviews on G2 and users believe it is a time-saving product with the ease of making scalable products. 

The abovementioned graph databases are some of the leading technologies but there are other players in this industry. 


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