[wiremine]

Does ArangoDB use the same storage strategy MongoDB does? From the FAQ:

"So how much RAM do you need? This depends on the size and structure of your data: Your application will access one or many collections (think of collections as denormalized tables for the time being). Once you open a collection the indexes for this collection are created in the RAM and the data is loaded into the RAM using memory-mapped files. If your collections are bigger than your RAM, the operation system will be forced to swap data in and out of the swap space."

I'm not an expert, but a lot of people seem to harp on MongoDB for this very reason. Does ArangoDB use the same strategy? If not, how is it similar/different?

[bjerun]

In principle, ArangoDB behaves similarly to MongoDB here. Both are essentially "mostly-in-memory" databases in the sense that they hold the data in memory and persist it at the same time to disk via memory mapped files. This approach is good for performance and if you run out of RAM you ought to shard your data.

However, MongoDB often uses a lot of memory for the actual data, since its BSON binary format stores the names of the attributes with every single document. ArangoDB detects similar shapes of documents (see https://www.arangodb.com/faq#how-do-shapes-work-in-arangodb) and thus avoids this particular problem.

[wormit123]

I have been bitten by this using MongoDB as well. The shape recognition of ArangoDB sounds very useful. If this works well, it would alleviate a problem that NoSQL solutions so far have in comparison to classical relational databases.