81–90 of 119 posts
With this release aggregation framework got super powerful. Now it returns a cursor. Now we can get the aggregation results and iterate over them. No more 16mb result limitation as well...
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I don't know anything about MongoDB but can you give an example where DB level locking is a problem?
High volume of writes
A lot of hype... And we still have db level locking. If document level is too difficult, at LEAST do collection level (not that it is too much better, but least it some real improvement).
How do the two databases compare now. Is search improving in Mongo or is that something they are not really worrying about at the moment.
I've been using Elasticsearch as a primary database for my new project, which has basically been a good NoSQL db that happens to have great search. However, peripheral tools(performance testing, hosting) have been a bit rough. How do the two databases compare now. Is search improving in Mongo or is that something they are not really worrying about at the moment.
mongodb is the best database in the whole wide world at the moment. I encourage everyone to jump in mongodb for agile web scale development with full big data capability.
Well, I think I must disagree with you in here. I'm sure that it is a viable choice for some use cases, it's just that I didn't found a use case for it yet. Being able to choose from PostgreSQL, Redis, Cassandra, heck, even ElasticSearch made me always choose one of those over MongoDB, at least for the problems which I had been trying to solve.
Can someone with more MongoDB experience give me your thoughts on the upgrade difficulty here? Worth doing soon, or waiting for a point release? Does this require a data rebuild/update process (coming from 2.4)?
IMO unless you desperately need one of the new features I would hold off a few weeks. With a release this big I'd expect there will be some bugs and wouldn't be surprised to see 2.6.1 shortly.
A lot of hype... And we still have db level locking. If document level is too difficult, at LEAST do collection level (not that it is too much better, but least it some real improvement).
"Finally, MongoDB 2.6 lays the foundation for massive improvements to concurrency in MongoDB 2.8, including document-level locking." They hear you and are working on it.
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mmap does complicate things. A traditional database often works using write ahead logs. The log holds changes made to the database over time - so when you want to write a change to your DB, you put 'I'm changing value x.y to 50' in your WAL. Sometime later the actual data pages holding the modified x data structure can be written out to disk. If you have a crash before the data pages get written out, you can 'replay'…
Just to note, the MongoDB journal is basically a write ahead log and has been around since 1.8. It's not simple, you are correct, and involved remapping portions of memory privately, and leads to some inflated numbers on the virtual memory reporting side. There's a great write up here: http://blog.mongodb.org/post/33700094220/how-mongodbs-journa...
I've been using Elasticsearch as a primary database for my new project, which has basically been a good NoSQL db that happens to have great search. However, peripheral tools(performance testing, hosting) have been a bit rough. How do the two databases compare now. Is search improving in Mongo or is that something they are not really worrying about at the moment.
In terms of how they compare, I'm not familiar enough with Elasticsearch to comment, but for basic test searching needs, the implementation in MongoDB is pretty decent. More here: