ArangoDB is good Database option for Developers and Datascients
July 02, 2021

ArangoDB is good Database option for Developers and Datascients

Pavan sreevatsav Akula | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with ArangoDB

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.
  • 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
  • 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
  • AQL Query Language
  • Multi-Model Powered Machine Learning
  • Cloud – On-Prem – Anywhere
  • It is very powerful tool and should adv more to improve sales
  • Should conduct more free trails and trainings
  • Open source and runs everywhere
It uses AQL query Language, which is different from other Databases.
It has flexibility to integrate in cloud, on-prem anywhere

Do you think ArangoDB delivers good value for the price?

Yes

Are you happy with ArangoDB's feature set?

Yes

Did ArangoDB live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of ArangoDB go as expected?

Yes

Would you buy ArangoDB again?

Yes

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.