Neo4j Alternatives

Introduction to Neo4j Alternatives

Neo4j is a graph database management system, released in 2007. Neo4j is implemented in java language and can accessible from software written in other languages using cypher query language through transaction HTTP endpoint or through binary bolt Protocol. In Noe4j, data or information stored in formats like edge, node or attribute. Edge and nodes can have any number of attributes, both can be labelled. Labels are used for narrow searches. There are other alternatives available for Neo4j which provide similar functionalities. Here in this article, we are going to discuss these alternatives.

List of Neo4j Alternatives

Below is the list of neo4j alternatives.

• ArangoDB

It is a distributed free and open-source database system. This database system supports three data models like document, key/ value, and graph with one database core and unified query language AQL. AQL stands for ArangoDB Query language. With ArangoDB we can declare a combination of different data access patterns in single query. While working with graph data, it provides scalable queries. Using Foxx framework, ArangoDB integrates with native Javascript libraries directly.

• OrientDB

It is a distributed graph database system that provides flexibility of document database. It is an open-source NoSQL database management system. It supports models like graph, document, key/value, and object. Relationships are managed as in graph database with direct connection between records. It supports three types of modes namely schema-less, schema full, and schema mixed. OrientDB is implemented using pure java language, therefore, it can run on any systems like windows, Mac OS, or Linux with Java virtual machine (JVM). It can develop in Cloud. It supports various cloud providers like Microsoft Azure, AWS (Amazon Web services), DigitalOcean.

• Cassandra

It is a free and open-source distributed NoSQL database management system designed to handle a large amount of data across many accomidity servers. Its distributed architecture is tailored for multi-data center deployment, redundancy, for failure, and disaster recovery. It introduced CQL which means Cassandra query language is an interface to access the Cassandra as an alternative to the traditional SQL language. Cassandra replicate data automatically to multiple nodes for fault tolerance. Replication strategies are configurable. It is a hybrid between key value and tabular database management system.

• HyperGraphDB

HyperGraphDB is a general-purpose Database management system design based on a powerful knowledge management formalism known as a direct hypergraph. For knowledge management, mostly persistent memory model is designed, Artificial intelligence and semantic web projects, a bit can also be used as embedded object-oriented database for java projects of all sizes.

• Azure cosmos DB

It is Microsoft’s distributed, multi-model database management system designed for managing data at planet scale. Generally, azure cosmos DB is classified under NoSQL database. It stores items in containers, containers are grouped in databases which are analogous to namespaces above container. Every field in each item is automatically indexed. At container level, TTL (Time to live) is specified to automatically delete the items after a certain amount of time expressed in seconds. Countdown starts immediately after the last update of the item.

• Redis

It is a remote dictionary server used as a distributed, in-memory key-value database. It supports various kinds of abstract data structure such as lists, maps, string, bitmap, streams, spatial indexes. It provides master replica replication. Data from any media server can replicate to any number of replicas. One replica can be a master to the other replica. This allows implementation of single-rooted replication tree. The Cluster can scale up to 1000 nodes. Organization like Twitter, Amazon Web Services, Microsoft, and Alibaba are using Redis. Redis can be used for session caching, message queue application, full page cache, etc

• Oracle Spatial and graph

It supports full range of geospatial data and analytics for land management and geographic information systems, transportation, mobile location services, Lidar analysis, sales territory management, and location-enabled business intelligence. Its graph features include RDF graphs for applications ranging from semantic data integration to social networking analysis to linked open data and network graphs used in transportation, utilities, energy, telcos and drive time analysis for sales and marketing applications.

• DGraph

It shares data to horizontally scale to hundreds of servers, designed to minimize the number of disk seeks and network calls. It is built like search engine. Queries are broken down into sub-queries which run concurrently to achieve low latency and high throughput. It can easily scale to multiple machines or data centers. Its sharded storage and query processing were specifically designed to minimize the number of network calls.

Conclusion

In this article, we have seen Neo4j alternatives along with their features and uses. You can choose any of them based on your requirements. We hope you will find this article helpful.

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