This is a good read, claiming: "Relational Databases Aren't Dead. Heck, They're Not Even Sleeping", http://readwrite.com/2013/03/26/relational-databases-far-from-dead. A key quote:
"While not comprehensive, the uses for NoSQL databases center around the acquisition of fast-growing data or data that does not easily fit within uniform structures."
There were 2 parts in the statement about NoSQL's uses. I'll start with the latter:


"data that does not easily fit within uniform structures" - NoSQL is probably the right choice, hmm although I always encourage thinking and architecting in advance. And also online structure changes do exist in the RDBMS world and recently in MySQL: …

We recently resumed our discussion around bringing Fractal Tree indexes to MongoDB.  This effort includes Tokutek’s interview with Jeff Kelly at Strata as well as my two recent tech blogs which describe the compression achieved on a generic MongoDB data set and performance improvements we measured using on our implementation of Sysbench for MongoDB.  I have a full line-up of benchmarks and blogs planned for the next few months, as our project continues.  Many of these will be deeply technical and written by the Tokutek developers.

We have a group …

During the second half of our CUBE discussion with Wikibon analyst Jeff Kelly at this year’s Strata Conference in Santa Clara, we talked about the tipping point for Big Data. Strata veterans could see at a glance that this year’s conference was markedly different. No longer the exclusive domain of geeks and database administrators, this year’s Strata featured some of the biggest enterprise vendors around. With heavy weight enterprise players Intel and EMC Greenplum announcing their own Hadoop distributions, big data is clearly going mainstream. Now that we know how to capture, store, access and analyze big data, what’s the next step? Listen in to hear my conversation with Jeff Kelly about taking big data down its last mile and finally putting it in the hands of business users.

Source: …

We had the opportunity to do a CUBE interview with Wikibon analyst Jeff Kelly at last week’s Strata Conference in Santa Clara. In the first part of our conversation, we discuss how our success in integrating Tokutek’s Fractal Tree® technology into MySQL has led us to another popular database, MongoDB. We explain the results of our recent benchmarking tests with MongoDB, which indicate that adding indexing can also improve performance for this popular NoSQL database with faster insertion rates, lower query latency and greater …

One doesn’t have to look far to see that there is strong interest in MongoDB compression. MongoDB has an open ticket from 2009 titled “Option to Store Data Compressed” with Fix Version/s planned but not scheduled. The ticket has a lot of comments, mostly from MongoDB users explaining their use-cases for the feature. For example, Khalid Salomão notes that “Compression would be very good to reduce storage cost and improve IO performance” and Andy notes that “SSD is getting more and more common for servers. They are very fast. The problems are high costs and low capacity.” There are many …

I’ve said it before, and, as is the nature of these things, I’ll almost certainly say it again: your database performance is only as good as your indexes.

That’s the grand thesis, so what does that mean? In any DB system — SQL, NoSQL, NewSQL, PostSQL, … — data gets ingested and organized. And the system answers queries. The pain point for most users is around the speed to answer queries. And the query speed (both latency and throughput, to be exact) depend on how the data is organized. In short: Good Indexes, Fast Queries; Poor Indexes, Slow Queries.

But building indexes is hard work, or at least it has been for the last several decades, because almost all indexing is done with B-trees. That’s true of commercial databases, of MySQL, and of most NoSQL solutions that do indexing. (The ones that don’t do …

ClearStory sheds light on data analysis service. Illuminating ‘dark data’. More.

For 451 clients: ClearStory bags $9m in series A funding, sheds light on its data analysis service bit.ly/Y6v8sV By Krishna Roy

— Matt Aslett (@maslett) February 12, 2013

For 451 clients: Global IDs makes ‘big data’ MDM play via cloud and Hadoop, touts profitable growth bit.ly/Y6v6kL By Krishna Roy

— Matt Aslett (@maslett) February 12, 2013

ScaleBase releases version 2.0 of its MySQL database scalability software bit.ly/WGtEtN

— Matt Aslett (@maslett) …

“With MySQL 5.6, developers can now commingle the “best of both worlds” with fast key-value look up operations and complex SQL queries to meet user and application specific requirements” –Tomas Ulin. On February 5, 2013, Oracle announced the general availability of MySQL 5.6. I have interviewed Tomas Ulin, Vice President for the MySQL Engineering team [...]

One of the most complicated aspects of putting together our database landscape map was dealing with the growing number of (particularly NoSQL) databases that refuse to be pigeon-holed in any of the primary databases categories.

I have begun to refer to these as “multi-model databases” in recognition of the fact that they are able to take on the characteristics of multiple databases. In truth though there are probably two different groups of products that could be considered “multi-model”:

True multi-model databases that have been designed specifically to serve multiple data models and use-cases

Examples include:
FoundationDB, which is being designed to support ACID and NoSQL, but more to the point …

One of our training courses has a section covering MySQL's Memcached API, and how it works. In the discussion, there's a line that goes like this:

 "A key is similar to a primary key in a table, and a value is similar to a second column in the same table"

For someone well versed in database tables but not so much in key-value stores, that sentence might take a bit of grasping. So, let's break it down.

An Example Key/Value Store 

Imagine the table kvstore has a column key and a column value. Also imagine that we've set up the Memcached plugin in MySQL and configured it to use that table and those columns as its store. I won't get into that bit for now, but trust me, it's not that hard.

You might be familiar with statements like this:

REPLACE INTO kvstore (key, value) VALUES ('X', 'Y');
SELECT value FROM kvstore WHERE key='X';

Now imagine you want to be …