PostgreSQL vs ArangoDB

PostgreSQL performance increases with each release, this is also proven by many benchmark tests.

Notable performance features include:

• As PostgreSQL only supports one storage engine, it has been able to integrate and optimise it and with the rest of the database. This has resulted in multiple benefits such as the ability to allow different transaction types to co-exist efficiently without the need to select storage engine types once for each table ahead of time.

• On the fly data compression resulting in less IO required for reading.

• Asynchronous + synchronous Replication.

• PostgreSQL supports a asynchronous API for use by client applications. It is reported to increase performance by up to 40% and is not supported by MySQL.

• Designed to scale very well with large numbers of cores at high concurrency levels.

PostgreSQL is known to have a very holistic approach to robustness and data integrity which is reflected by it being fully ACID compliant.

PostgreSQL has always been strict about making sure data is valid before allowing it into the database, and there is no way for a client to bypass those checks.

Depending on your requirements, ACID compliance might be important.

PostgreSQL has a strong community backing it, with guides, tutorials and support for any kind of problem a developer may have.

JSON data can be stored as a column with optional indexes. In 9.4 (upcoming at the time of this writing), JSONB will be a binary version of JSON that will save space. It's like the best of the NO-SQL world without having to give up ACID and Relationships. This means that cascading deletes can be done in a single Transaction across multiple JSON documents.

Regular fixes and features are released

PostgreSQL can be extended to have geographic object support through PostGIS and allows for location queries to be run through SQL.

There are many packages (like Sequelize) that integrate deeply with the features Postgres offers.

Postgres supports popular languages for coding stored procedures, such as Perl and Python. So, you can fairly easy transform just DB-server to reliable Service with complex business logic.

It is a powerful, open source product that has all the bells and whistles when compared with its costly, proprietary counterparts.

You can model your data as documents or as a graph - no data model lock-in. You can even combine both models and use them in a single AQL query.

Unlike many NoSQL databases, ArangoDB does support joins in AQL queries.

You can extend ArangoDB using JavaScript that runs directly on the Server (Google V8). You can build data-centric microservices that aggregate, validate, transform or enrich data (It's up to you, plain JavaScript) and provide those via a custom API route.

You can use ACID Transactions for short and small data retrieval and/or modification operations in ArangoDB.

ArangoDB has a very good Java Driver for synchronous and asynchronous. In addition the team there is working on a Spring Data integration.