FYI you can store unstructured data in PostgreSQL (and query it) with the introduction of hstore. So knock one more reason to use MongoDB instead of PostgreSQL off your list. (Disclaimer: the length of my list to use MongoDB has always been a constant that is less than one.)<p><a href="http://www.postgresql.org/docs/9.1/static/hstore.html" rel="nofollow">http://www.postgresql.org/docs/9.1/static/hstore.html</a>
This is pretty cool but I'm struggling to see what the use cases are, atleast for analysis. There might be quite a bit of benefits for running application code that I'm not aware of. With regards to analysis though, their own example question is "what happened last night?" but then they go on to say that it is a near real-time data store. Does it matter that it is a real-time mirror then?<p>I've always liked the paradigm of doing analysis on "slower" data stores, such as Hadoop+Hive or Vertica if you have the money. Decoupling analysis tools from application tools is both convenient and necessary as your organization and data scales.
Reading the headline I thought they were introducing a SQL like interface to their API, sort of like FQL for Facebook and I got a little excited. Something like this to get the email addresses of all your active trial subscribers:<p>SELECT c.email FROM customers c, subscriptions s WHERE c.subscription_id = s.id AND s.status = "active" and s.trial_start IS NOT NULL;<p>(where of course the customer and subscription tables would be a virtual view on your customers and subscriptions)
10gen also has a nice python app which syncs by tailing the MongoDB oplog to an external source. Most common is Solr.<p><a href="https://github.com/10gen-labs/mongo-connector/tree/master/mongo-connector" rel="nofollow">https://github.com/10gen-labs/mongo-connector/tree/master/mo...</a><p>Seems to be high quality, and supports replica sets.
Very neat project. I can see several use-cases for this where I work- It'd be nice to have alternatives means of searching through data.<p>I'd also like to mention a project I've been contributing to, Mongolike<p>[My fork is at <a href="https://github.com/e1ven/mongolike" rel="nofollow">https://github.com/e1ven/mongolike</a> , once it's merged upstream, that version will be the preferred one ;) ]<p>It implements mongo-like structures on TOP of Postgres. This has allowed me to support both Mongo and Postgres for a project I'm working on.
I thought that "young" NoSQLs sometime in will got SQL interface.<p>Look at old NoSQLs: Intersystems Cache got SQL interface, GT.M (in PIP-framework) also got SQL.<p>My impression that MongoDB looks a lot like MUMPS storage with globals in JSON.
Is there currently support for "unrolling" arrays or hashes into tables of their own? If not, would definitely be interested in helping to add that on (we use arrays on documents quite a bit, but have run into a number of situations where a simple SQL query for analysis could have quickly replaced a bunch of mongo scripts).
If you need to make a tool(and use twice the amount of storage) to be able to "query your data" in a SQL manner while using noSQL, it probably means you are using the wrong tool for the job.
Author of MoSQL, did you consider just using the MongoDB FTW instead? <a href="https://github.com/citusdata/mongo_fdw" rel="nofollow">https://github.com/citusdata/mongo_fdw</a>
I love this idea. I can see myself using MoSQL pretty soon. Does it handle geospatial data? Can it replicate geospatial data from Mongo to a Geometry data type in Postgres?
<i>MongoDB is great for a lot of reasons</i> - record-level locking? multiple concurrent writes? append-only journals?<p>I have read than in version 2.x they announce some features, so, it is greatness?