ArangoDB vs. H2 Database Engine

Use cases provided by default are good and can be improve better using Machine Learning and AI. AQL query language is very simple and efficient in use if anyone using SQL can quickly learn AQL Language.

Developers can easily map the database and can access various patterns like search, ranking.

JSON and semantic search is the latest and next-generation technology to implement to access and extract large datasets.

Incentivized

For running application tests it's well suited. H2 [Database Engine] can replace the real-world database solution for them easily and removes the requirement to set up a a separate database instance just for running unit tests. For using in actual production application one needs to consider scale. H2 is suitable if application runs in single instance and database is located in same machine as a file where that application runs. This means the application shouldn't have a large user base. However it's easy to switch to an actual MySQL instance if the need arises, it's most likely only a configuration change and doesn't require new code.

Incentivized

• AQL query language is big plus for ArangoDB
• It can be implemented cloud as well as on-prem
• Search Engine is a very good option for ArangoDB

Incentivized

• Can run as an in-memory database.
• Simple and quick to get started with, and is light weight (only 2MB).
• SQL compliant so it compatible with most relational databases.

Incentivized

• By providing the free services for few months will be help understand for beginners
• Enhancing features in dashboard and can make UI more user-friendly
• Should conduct more surveys and adv to improve scalability

Incentivized

• There's a warning in official FAQ "Is it Reliable?"-section which makes it seem like H2 is not yet a mature product.
• If raw SQL queries are used there maybe be differences between MySQL & H2. ORM library should be used.
• Support seems to be community-based only.

Incentivized

It uses AQL query Language, which is different from other Databases. It has flexibility to integrate in cloud, on-prem anywhere

Incentivized

While both can run as an in-memory database, H2 Database Engine was just so much easier for us to use since we primarily use the Java stack and H2 Database Engine is also built with Java.

Incentivized

• It is very powerful tool and should adv more to improve sales
• Should conduct more free trails and trainings
• Open source and runs everywhere

Incentivized

• Doesn't take time from developers, once it's configs are set up for testing it works in everyone's development environments
• Easy to integrate in application, no need to setup separate database software, no maintenance
• No need to deal with infrastructure related issues/costs - database runs in same machine as the application that uses it.

Incentivized