With data volumes exploding, it is vital to be able to ingest and query data at high speed. For this reason, MySQL has implemented NoSQL interfaces directly to the InnoDB and MySQL Cluster (NDB) storage engines, which bypass the SQL layer completely. Without SQL parsing and optimization, Key-Value data can be written directly to MySQL tables up to 9x faster, while maintaining ACID guarantees.

In addition, users can continue to run complex queries with SQL across the same data set, providing real-time analytics to the business or anonymizing sensitive data before loading to big data platforms such as Hadoop, while still maintaining all of the advantages of their existing relational database infrastructure.

This and more is discussed in the latest Guide to MySQL and …

This post shows the construction process of the Syslog Audit plugin that was presented at MySQL Connect 2012. It is based on an environment that has the appropriate development tools enabled including gcc,g++ and cmake. It also assumes you have downloaded the MySQL source code (5.5.16 or higher) and have compiled and installed the system into the /usr/local/mysql directory ready for use. 

The information provided below is designed to show the different components that make up a plugin, and specifically an audit type plugin, and how it comes together to be used within the MySQL service. The MySQL Reference Manual contains information regarding the plugin API and how it can be used, so please refer there for more detailed information. The code in this post is designed to …

The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability.

Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs.

First, a little bit about why we developed these APIs and why they are interesting to Java developers.

ClusterJ and Cluster JPA

ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, …

Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful.

Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar.

Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL:

- On-Demand webinar

- …

In a previous post, I demonstrated a simple Python database API with a syntax similar to jQuery. The goal was to provide a simple API that would allow Python programmers to use a database without having to resort to SQL, nor having to use any of the good, but quite heavy, ORM implementations that exist. The code was just an experimental implementation, and I was considering putting it up on Launchpad.
I did some basic cleaning of the code, turned it into a Python package, and pushed it to Launchpad. I also added some minor changes, such as introducing a define function to define new tables instead of automatically creating one when an insert was executed. Automatically constructing a table from values seems neat, but in reality it is quite difficult to ensure …

There has been a lot of discussions lately about various non-SQL languages that provide access to databases without having to resort to using SQL. I wondered how difficult it would be to implement such an interface, so as an experiment, I implemented a simple interface in Python that similar to the document-oriented interfaces available elsewhere. The interface generate SQL queries to query the database, but does not require any knowlegdge of SQL to use. The syntax is inspired by JQuery, but since JQuery works with documents, the semantics is slightly different.

A simple example would look like this:

from native_db import *
server = Server(host='127.0.0.1')
server.test.t1.insert({'more': 3, 'magic': 'just a test', 'count': 0})
server.test.t1.insert({'more': 3, 'magic': 'just another test', 'count': 0})
server.test.t1.insert({'more': 4, 'magic': 'quadrant', 'count': 0}) …

At OSCON 2011 last week, Oracle delivered more early access (labs) features for MySQL 5.6 replication. These features are focused on better integration, performance and data integrity:

- The Binlog API: empowering the community to seamlessly integrate MySQL with other applications and data stores;

- Binlog Group Commit and Enhanced Multi-Threaded Slaves: continuing to deliver major improvements to replication performance;

- Durable Slave Reads: further enhancing data integrity.

These new features build on the significant replication enhancements announced as part of the MySQL 5.6.2 Development Milestone Release back in April.

We are always listening to our customers and community. And, based on their needs and input, the MySQL engineering team continues to take …

I hope everyone is enjoying summertime, at least in the northern hemisphere. I’m about to head out to the pool, but before I go, here is a summary of this week’s blog posts.

1. Introduction to Perl interface for Monitis API
Monitis announces a simple way to access its API through Perl, a high-level, general-purpose, interpreted, dynamic programming language. This post demonstrates some examples for using the API with Perl and describes some of the benefits of the programming language. The source can be found on our Github page.

2. 101 Tips to MySQL Tuning and Optimization …

The elmcity service connects to a half-dozen other services, including Eventful, Upcoming, EventBrite, Facebook, Delicious, and Yahoo. It's nice that each of these services provides an API that enables elmcity to read their data. It would be even nicer, though, if elmcity didn't have to query, navigate, and interpret the results of each of these APIs in different ways.

For example, the elmcity service asks the same question of Eventful, Upcoming, and EventBrite: "What are the titles, dates, times, locations, and URLs of recent events within radius R of location L?" It has to ask that question three different ways, and then interpret the answers three different ways. Can we imagine a more frictionless approach?

I can. Here's how the question might be asked in a general way using the Open Data Protocol (OData):

 …

Okay… So I’ve blogged many times before about the Storage Engine API in Drizzle. This API is somewhat inherited from MySQL. We have very much attempted to make it a much cleaner interface. Our goals in making changes include: make it much easier to write and maintain a storage engine, make the upper layer code obviously correct and clear in what it’s doing and being able to more easily introduce optimisations.

I’ve recently added a Storage Engine that is only used in testing: storage_engine_api_tester. I’ve blogged on it producing call graphs (really state transition graphs) before both for Storage Engine and Cursor.

I’ve been expanding the test. My test engine is now a wrapper around a real engine instead of just a fake one. …