It was simple to setup and was easy to understand. Now whenever we got some issue, the customer support was always their to tackle the issue. Now after the setup of arrango the frequent use of it between developer has increase and because of the its wide range of features we could integrate it easily.

There were not such dislikes but somewhere accessing the data was not an cakewalk.

A single place to store all the data

The compatibility between the looseness of schema-less design and the flexibility as a graph database is excellent. The ability to write JSON-first queries using AQL. Conveniently includes a rich Web UI. It is equipped with a full-text search engine that is relatively easy to use.

It seems unavoidable due to performance reasons, but management and operations on collections and databases using AQL are weak. If there were more capabilities for operations on collections and databases, the possibilities would expand.

It is used to support designs where the elements to be managed have dynamically variable attributes and require numerous relationships. By leveraging the strengths of document databases and graph databases, it addresses issues such as the lack of a fixed schema and complex relationships, which could become bottlenecks in conventional databases.

Arango DB was suggested to me by my seniour as it's open source and provide a great platform for graph databases, It was very user friendly for a graph database, it was very easy to create vetices for the graph visuallise them in my local container and there after making edge definition and connecting them saved me so much time for initial POC with graph RAG.

Documentation for the DB can be better with a section of website dedicated only Documentation in details i found myself going website to website finding the things i needed for my use case other than that it was really good.

Being an Open Source DB it's solving the problem of not being expensive for starters there after it's beginer freindly implementation can be learned by freashers and can easily be incorporated to prodution grade systems. Being in an early stage startup it helped me to do my initial POC very fast and helped me with my research on Graph RAG

It is simple. Much better than Mongo. Treating edges as collection, I believe a mster stroke. Enables both graph and document DB at a time

Nothing at time point. Probabaly not yet being comoatiable Gremilian?

We have a situation where the meta-data about our solution has complex relationships. At each node, the data needs to be schemaless. We also may need to do traverse the graphs in multiple complex ways. And, do so quickly and have the ability to hos this data platform within our cluster.

Its comprehensible. The tutorials are really great, we can fastly have access to the power of graph databases.

For the moment, as it is my begining, I do not have any "dislikes" on the subject.

It is used in our clinical data warehouse.

The fact that ArangoDB is open access and can interact with other tools

The graphical aspect in not really taken in account

The problem of visualiztion of complex data for my reaserch output

I like that ArangoDB allows us to start a subcription free to kinda test the databases first. I think the upside to using ArangoDB is that there are plenty of choices.

I cannot say to much about dislike ArangoDB but maybe to many options to choose from but I am not sure that a bad thing.

It provides me with a graph exploration tool thats designed to tranform the way I deal with datasets.

The query language is simple and makes sense the graph presentation is nice Using the SDK is fine

The editor is not good the shortcuts are lame no auto complete creating application apis with specific permission is bad, slow

Saving the data as a graph. Allowing to traverse data on a graph

- query language - support - scalability - innovation - made in germany

- learning curve is kind of steep - example and tutorials are there for simple stuff, but really complex queries are somewhat a challenge

ArangoDB's query language and graph model is solving the problem that SQL queries are getting insanely long and uncomprehensible. The Multi model approach is solving the issue that traditionally different data storages where needed, now we can span different models inside a single db.

We recently transitioned from a self-hosted version of ArangoDB to ArangoDB Graph (their managed offering), and the experience has been smooth and efficient. The ArangoDB team was helpful throughout the migration process, providing clear guidance and timely support to address our questions and ensure a successful transition. ArangoDB itself provides a database that supports all the basics you'd expect from a graph database system, and a lot of convenient functionality like a unified query language that can handle both graph and relational-style queries.

Because of the unified query language, there is a degree of lock-in, but this is true of all database systems if you take advantage of anything other than the most basic features.

We use ArangoDB to assemble and explore relationships between different entities, meaning we can spend our engineering effort delivering new features rather than thinking about graph traversal algorithms and the like.