I'm relatively new to NoSQL databases and I have to evaluate different NoSQL-Solutions for a monitoring tool.
The situation is the following: One datum is just about 100 Bytes big, but there are really a lot of them. During a day we get about 15 million records... So I'm currently testing with 900 million records (about 15GB as SQL-Insert Script)
My question is: Does Couchdb fit my needs? I need to do range querys (on the date the records were created) and sum up some of the columns acoording to groups definied by "secondary indexes" stored in the datum.) I know that MapReduce is probably the best solution to calculate that, but is the JavaScript of CouchDB able to do this in an acceptable time?
I already tried MongoDB but it's really poor MapReduce made a crappy job... I also read about HBase and Cassandra. But maybee CouchDB is also a good possibility
I hope I gave you all the needed information... Thank you for your help!
andy
Oracle Database Oracle has provided high-quality database solutions since the 1970s. The most recent version of Oracle Database was designed to integrate with cloud-based systems, and it allows you to manage massive databases with billions of records. Traditionally, Oracle has offered RDBMS solutions.
The default value for many OSes is 1024 or 4096. On a system with many databases or many views, CouchDB can very rapidly hit this limit.
Frankly, at this time, unless you have very good hardware, Apache CouchDB may run into problems. Map/reduce will probably be fine. CouchDB's incremental map/reduce is ideal for your requirements.
As a developer, you will love it! Unfortunately as a sysadmin, you may notice more disk usage and i/o than expected.
I suggest to try it. Being HTTP and Javascript, it's easy to do a feasibility test. Just remember, the initial view build will take a long time (let's assume for argument it takes longer than every other competing database). But that time will never be spent again. Map/reduce runs only once per document (actually per document update).
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