Werner Vogels:

Following the huge success of being able to provision a consistent, user-requested I/O rate for DynamoDB and Elastic Block Store (EBS), the AWS Database Services team has now released Provisioned IOPS, a new high performance storage option for the Amazon Relational Database Service (Amazon RDS). Customers can provision up to 10,000 IOPS (input/output operations per second) per database instance to help ensure that their databases can run the most stringent workloads with rock solid, consistent performance.

Amazon is the first company I know of championing guaranteed performance SLAs. Until recently most of the SLAs were referring to availability, resilience, and redundancy. But soon performance-based SLAs will become the norm for other service providers. I’d also expect appliance vendors to be asked for similar guarantees sooner than later.

Original title and link: Provisioned IOPS for Amazon RDS (NoSQL database©myNoSQL)

via: http://www.allthingsdistributed.com/2012/09/provisioned-iops-rds.html

Gabor Vitez:

With a new post hitting Hacker News again on MySQL’s memcached plugin, I really wanted to do a quick-and-dirty benchmark on it, just to see what good it is – does this interface offer any extra speed when compared to SQL+ActiveRecord? Does it have it’s place in the software stack? How much work is needed to get this combination off the ground?

When running into micro-benchmarks, I really try my best to figure out if they hide any value. But it’s hard to find any in one that uses different libraries, runs both the benchmark and the server on the same machine and uses no concurrency.

Original title and link: A Quick Test of the New MySQL Memcached Plugin With (J)Ruby (NoSQL database©myNoSQL)

via: http://elevat.eu/blog/2012/08/a-quick-test-of-the-new-mysql-memcached-plugin-with-ruby/

Ronald Speelman:

You can use this MySQL function to generate names, (e-mail)addresses, phone numbers, urls, bit values, colors, IP address, etc.. As usual, the code is provided in a zipfile and the code is fully documented.

The last couple of days I’ve been looking for generating some good test data in JSON format¹, so if you are aware of something please drop me a note.

Original title and link: Generating Meaningful Test Data Using a MySQL Function (NoSQL database©myNoSQL)

via: http://moinne.com/blog/ronald/mysql/howto-generate-meaningful-test-data-using-a-mysql-function

Domas Mituzas about the MemSQL vs MySQL benchmark:

Though I usually understand that those claims don’t make any sense, I was wondering what did they do wrong. Apparently they got MySQL with default settings running and MemSQL with default settings running, then compared the two. They say it is a good benchmark, as it compares what users get just by installing standard packages.

That is already cheating, because systems are forced to work in completely different profiles.

The first paragraph of the post summarizes very well the general feeling about benchmarks:

I don’t like stupid benchmarks, as they waste my time.

I think that most of the generic benchmarks are stupid, even if some generic numbers are considered interesting by software engineers. Benchmarks designed around specific scenarios of applications will most of the time give more realistic results. But even those are difficult to design and account for all the configuration options, scaling, or changes of the use cases.

Original title and link: MySQL Is Bazillion Times Faster Than MemSQL (NoSQL database©myNoSQL)

via: http://dom.as/2012/06/26/memsql-rage/

In short, if you try to authenticate to a MySQL server affected by this flaw, there is a chance it will accept your password even if the wrong one was supplied. The following one-liner in bash will provide access to an affected MySQL server as the root user account, without actually knowing the password.

  $ for i in `seq 1 1000`; do mysql -u root --password=bad -h 127.0.0.1 2>/dev/null; done

Don’t try this at home. Or if you try it, don’t tell anyone the result.

Original title and link: A Tragically Comedic Security Flaw in MySQL (NoSQL database©myNoSQL)

via: https://community.rapid7.com/community/metasploit/blog/2012/06/11/cve-2012-2122-a-tragically-comedic-security-flaw-in-mysql

Jetpants:

Today, we’re happy to announce the open source release of Jetpants, Tumblr’s in-house toolchain for managing huge MySQL database topologies. Jetpants offers a command suite for easily cloning replicas, rebalancing shards, and performing master promotions. It’s also a full Ruby library for use in developing custom billion-row migration scripts, automating database manipulations, and copying huge files quickly to multiple remote destinations.

This toolkit helps Tumblr manage its 60bn rows totaling 21TB of data in a MySQL cluster.

Original title and link: Tumblr Jetpants: A Toolkit for Huge MySQL Topologies (NoSQL database©myNoSQL)

via: http://engineering.tumblr.com/post/24612921290/jetpants-a-toolkit-for-huge-mysql-topologies

Have you ever tried to kill a query, but rather than just go away, it remained among the running ones for an extended period of time? Or perhaps you have noticed some threads makred with killed showing up from time to time and not actually dying. What are these zombies? Why does MySQL sometimes seem to fail to terminate queries quickly? Is there any way to force the kill command to actually work instantaneously?

Bookmarked.

Marco Tusa

Original title and link: MySQL KILL Command: How It Works (NoSQL database©myNoSQL)

via: http://www.dbasquare.com/2012/05/15/why-do-threads-sometimes-stay-in-killed-state-in-mysql/

Jeff Dickey enumerates some of the new features available in PostgreSQL—schema-less data, array columns, queuing, full-text searching, geo-spatial indexing—concluding that PosgreSQL has now everything an application needs:

Postgres has taken the features out of all of these tools and integrate it right inside the platform. Now you don’t need to spin up a mongo cluster for non-rel data, rabbitmq cluster for queueing, solr box for searching. You can just have a single postgres server. That saves a huge ops headache since each of those clusters/boxes have to be durable, replicated, and scalable.

Sounds a bit too optimistic? As we’ve learned from the NoSQL space there are no silver bullets:

Now obviously, there’s a glaring downside with this approach: you get one box. Maybe a read slave or something, but really, you can’t scale it.

As you can imagine I disagree with most of the points, the only exception being that it is great to see so many useful features packaged with PostgreSQL—these are definitely going to make like easier for some of the developers.

But when talking about MySQL and NoSQL being done:

1. MySQL is done, except it has a huge community, there are tons of developers very familiar with it, and last but not least MySQL powers massive deployments. This last part matters a lot.
2. NoSQL is done, except many NoSQL solutions tackle different problem spaces providing optimal solutions for these by staying focused. Neither Oracle, nor MongoDB, nor PosgreSQL will be able to solve all problems. The wider range of problems they are covering, the less optimal solutions they are providing for corner case or extreme scenarios.

Original title and link: MySQL Is Done. NoSQL Is Done. It’s the Postgres Age (NoSQL database©myNoSQL)

via: http://dickey.xxx/mysql-is-done-it-s-the-postgres-age