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Which nosql system is better equipped for handling high volume inserts out of the box? Preferably, running on 1 physical machine (many instances allowed).
Has anyone done any benchmarks? (googling did not help)
Note: I understand that choosing noSQL database depends on what kind of data needs to be stored (document:MongoDB, graph:Neo4j, etc.).
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NoSQL databases allow developers to store huge amounts of unstructured data, giving them a lot of flexibility.
They are responsible for converting unstructured and semi-structured data into a format that analytics tools can use. Because of these distinctive requirements, NoSQL (non-relational) databases, such as MongoDB, are a powerful choice for storing big data.
As for speed, NoSQL is generally faster than SQL, especially for key-value storage in our experiment; On the other hand, NoSQL database may not fully support ACID transactions, which may result data inconsistency.
This means developers can be more agile. For example, developers using NoSQL databases can push code changes more quickly than they would be able to with relational databases. Cassandra, MongoDB, and Apache HBase are three of the most popular NoSQL databases currently available on the market.
If you want fast write speed, you can just insert your data into memory and flush data to the disc at a background every minute or so. That should be fastest solution.
MongoDB and Redis do this actually. For example, in mongodb you can go without journal enabled and writes will be very fast. But keep in mind that if you store data in memory at a single server there is possibility to loose your data (data that not flushed to the disc yet) when your server goes down.
In general, what database to use highly depends on data you want to store and task you are trying to solve.
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