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Support a query language designed for traversing data relationships.

The capabilities of a graph database will provide (at a minimum) the following benefits:

High performance and low cost of changeĪdopting a graph database technology for use cases fitting this profile will reduce complexity and overhead compared to using a relational database.

Querying relationships based on highly connected data.

Some of the graph database strengths the project needed were: I compared several NoSQL technologies and decided on a graph database implementation based on the project’s data needs. While there are many database implementations that fall under the NoSQL database umbrella, I ended up focusing on the Graph database subset. The data model needs to be flexible and easily accept new properties and relationships over time without requiring the modification of older data. The first release would primarily be a release to start collecting data. Since the client’s project was an internal project and starting a new space, data definitions were not well known and could drastically change over time. Current generation database technologies like NoSQL are designed around the idea of storing complex data relationships. Using a relational database, or other previous generation technologies, to store highly connected and complex data leads to poor performance, high change and maintenance costs, and excessively complex queries. The business value placed on data relationships has greatly increased and also strained many former data design strategies. Companies select database technologies to store data and relationships based on how IT needs it and the strengths of the database technology.Ĭompanies are increasingly storing data for relationship values. The industry has solved this data relationship storage issue by adopting polyglot database environments. While there is an industry need for relational databases, using a relational database for highly connected and complex data is problematic.

The client’s approved database base technology still surrounded relational databases. While this was an internal project, performance was still needed.

Due to the combination of performance and cost, I chose ArangoDB for my client’s needs.Ī recent project for a client required storing highly connected data and supporting queries to mine the complex data relationships.

In this post, I compare the benefits and risks of graph databases ArangoDB, Neo4j, and OrientDB for a client project.

Spoiler alert! Graph databases are a great option for storing complex and highly connected data.

Please keep that in mind as you read the post.

Security Best Practices in Application DevelopmentĪttention: The following article was published over 3 years ago, and the information provided may be aged or outdated.

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Our team is singularly comprised of software developers and architects-they are elite, vetted employees with strong histories of client acclaim. We build custom software solutions that solve complex business challenges.