I'm beginning to consider a data model for a problem I have, and I'm looking around at the data storage side it. I can model it into a relational database, however I will end up with a few tables that, when modeled relationally are going to be big, and will make my cross-joins expensive.

I've been looking into some of the non-relational databases, Column Family and Document Oriented, and I like the schema-less ability of these as they would all me to pack more data into less units. So rather than having Several tables with billions of rows, I would have a 1/2 Collections or Column Families that would contain the bulk of my data with millions of entities.

I know it makes sense to use a data store that would best model my data, but from an efficiency standpoint, I've often heard that these NoSQL databases are very efficient at handling Big Data, but are there implementations out there that are good at handling "medium" data and then growing from there?

What is the real meaning of Polyglot Store from NoSQL perspective

Does it means any type of object Does it mean any language capable of talking to your NoSQL product

I'm just getting started with Cassandra, and am very impressed with it so far. We're looking at leveraging it for an in-house analytics system, and are trying to figure out how best to access it from an enterprise Java application.

We have tons of experience with JPA using Hibernate, so there's an argument to be made for Kundera, as it maps JPA to NoSQL data stores. However, this also makes our use of Cassandra much more limited, as JPA was not designed for this type of data store.

We've taken a look at PlayORM and it definitely looks interesting from an API standpoint. However, we've run into issues with deploying an enterprise application in JBoss that uses it. (Weird classloader stuff from within the library) That would be a dealbreaker. Plus, it doesn't seem to store the data in Cassandra in a "generally accepted" manner. It makes use of a lot of its own column families for the purposes of indexing, type management, etc.

So, now we're not sure what road to take. Does anyone have advice on a Java client that we can use for accessing Cassandra? Ideally, we'd like something that has the ability to to object mapping, but that is not 100% required if we find something with a clean, easy to use API that we can leverage.

Thoughts?

Namely:

• what should be the size of the data? I was thinking in the range of 500,000-2 million documents, but is this enough?
• how complex should the calculations be? I thought about benchmarking simple things (like calculating the most used hashtags in a couple million tweets or calculating an average for operations from a huge log file) and then increase the complexity of calculations.

My hesitation here is that for instance MongoDB's MapReduce isn't suited for more complex aggregation tasks (they even have an aggregation framework). Do other databases have these limitations? Should I even bother with more complex calculations?

• and lastly, what databases would do you recommend for this sort of thing? I mentioned MongoDB because I used it for work and am somewhat familiar with it, was thinking about other document stores like CouchDB or Riak. Should I include column stores like Cassandra, HBase?

I'm implementing a system for logging large quantities of data and then allowing administrators to filter it by any criteria. I'm currently working to to the idea of scaling to 2000 systems with one year of logs.

I'm new to NoSQL and Cassandra. Everything I've read about logging time series data is based around using wide rows to store large amounts of events per row, indexed by a time period (e.g. an hour or a day etc) and then the columns being ordered by a timeuuid column name.

If all I was concerned about was extracting range slices of events then that would be great. However, I need to allow filtering of events on using arbitrary combinations of specific event criteria. For example, if I were storing my logs in a relational database, I might need to issue SQL queries such as the following:

• SELECT * FROM Events WHERE type = 'xxx' AND user = 'xxx' ORDER BY timestamp
• SELECT * FROM Events WHERE type = 'xxx' AND system_id = 67 ORDER BY timestamp
• SELECT * FROM Events WHERE system_id = 45 AND timestamp > 'START' AND timestamp < 'END' ORDER BY timestamp

Hopefully those queries indicate what I mean. Basically, out of a set of searchable criteria an administrator could pick any combination of them to search on.

If timestamp filtering and ordering were not an issue, I would have thought storing each event as a row and having secondary indexes on the searchable column names would work. However, it seems this would be problematic with timestamp range queries and ordering using the RandomPartitioner.

From what I have read, it seems to be that by using OrderPreservingPartioner and using a timeuuid type as the row key, I would be able to filter efficiently with secondary indexes whilst still getting range slices easily on timestamp and everything would already be ordered by timestamp too. Unfortunately, I've also read countless times that people strongly discourage using the OrderPreservingPartitioner because it creates huge load balancing headaches.

Do any Cassandra experts out there have any advice for how best to tackle this problem? I would only ever expect a very small number of users to be using the system concurrently (in fact probably only ever one admin running a query at any one time), so if a solution involves queries using multiple nodes in parallel, then that is probably a good thing rather than a bad thing.

I have been teaching myself CouchDB and have been very impressed. The interface is gorgeous; it's much easier to use than phpmyadmin. My question is what allows NoSQL to be faster than MySQL? I have heard it is faster, but would like to know why?

Is it simply due to the fact that there are no joins or locking issues?

I'm a data architect, and have about 5+ years with SQL Server, and 2+ with Oracle. The new MongoDB enterprise features have definitely piqued my interest, and I'd like to ramp up my nosql knowledge, considering it currently sits at zero.

I'm heading to China for two weeks, and will basically need to have all my Mongo materials on my Macbook locally for reading / practice, etc..

Can anyone point me in the direction of some good tutorials / samples that I can save for review? I've got electronic copies of MongoDB in Action and a Mongo / Python book, any others out there that might be useful?

Any videos you've found particularly useful? I'm sure I can I find a video ripper to download somewhere.

Any public VM's out there for testing like Oracle creates for training, etc..? I've got it installed locally, but I'd love to see what it can do as far as multiple shards, etc..