Oracle is the most powerful database system in the world. However, Oracle's expensive and complex replication makes it difficult to build highly available applications or move data in real-time to data warehouses and popular databases like MySQL. In this webinar you will learn how Continuent Tungsten solves problems with Oracle replication at a fraction of the cost of other solutions and with

Oracle is the most powerful database system in the world. However, Oracle's expensive and complex replication makes it difficult to build highly available applications or move data in real-time to data warehouses and popular databases like MySQL.

In this video (recording of our 9/13/12 webinar) you will learn how Continuent Tungsten solves problems with Oracle replication at a fraction of the

Earlier this week we all read GigaOM's article with this title:
"Why the days are numbered for Hadoop as we know it"I know GigaOM like to provoke scandals sometimes, we all remember some other unforgettable piece, but there is something behind it...

Hadoop today (after SOA not so long ago) is one of the worst case of an abused buzzword ever known to men. It's everything, everywhere, can cure illnesses and do "big-data" at the same time! Wow! Actually Hadoop is a software framework that supports data-intensive distributed applications, derived from Google's MapReduce and Google File System (GFS) papers.

My take from the article is this: Hadoop is a foundation, low-level platform. I used the word …

In my previous post,http://database-scalability.blogspot.com/2012/05/oltp-vs-analytics.html, I reviewed the differences between OLTP and Analytics databases.

Scale challenges are different between those 2 worlds of databases.



Scale challenges in the Analytics world are with the growing amounts of data. Most solutions have been leveraging those 3 main aspects: Columnar storage, RAM and parallelism.
Columnar storage makes scans and data filtering more precise and focused. After that – it all goes down to the I/O - the faster the I/O is, the faster the query will finish and bring results. Faster disks and also SSD can play good role, but above all: RAM! …

Inspired by a post from Juice Analytics.

We are a conflicted people. We love our TV and movie violence but worry that it ruins our children’s minds. We want to reduce healthcare costs, but don’t want to restrict the free market.

Conflicts like these leave little room for a satisfactory answer. Basic principles are in conflict and deeply-rooted desires run up against painful consequences. We

  Plug-in to Vegas The program focuses on key topics such as high availability, virtualization, security, business intelligence, Exadata, Cloud Computing and internals.  Recently added, we switched around the schedule to include the Thursday Deep Dive, Avoiding Downtime through the Maximum … Continue reading →

If you have used MySQL for some time you know that mysqld can write binlogs. This is usually used for backup purposes and JITR or for replication purposes so a slave can collect the changes made on the master and apply them locally.

Most of the time apart from configuring how long you keep these binlogs they are pretty much ignored.

Recently I came across an issue.  I have a slave server which is NOT configured read only and which has an additional database used to collect statistics from the replicated database and provided aggregation and business information. The typical sales per country, per product, per day, week, month, year, per whatever etc.  This is the usual datawarehouse type functionality.  It’s done on a slave and not the master so that the load is not passed on down stream to all boxes. …

Even though Data warehouse is picking very rapidly in the last year or so, but few companies who are already made a right mark in the right time could not[...]

At Kscope this year, I attended a half day in-depth session entitled Data Warehousing Performance Best Practices, given by Maria Colgan of Oracle. My impression, which was confirmed by folks in the Oracle world, is that she knows her way around the Oracle optimizer.

See part 1 for the introduction and talking about power and hardware. This part will go over the 2nd “P”, partitioning. Learning about Oracle’s partitioning has gotten me more interested in how MySQL’s partitioning works, and I do hope that MySQL partitioning will develop to the level that Oracle partitioning does, because Oracle’s partitioning looks very nice (then again, that’s why it costs so much I guess).

Partition – …

At Kscope this year, I attended a half day in-depth session entitled Data Warehousing Performance Best Practices, given by Maria Colgan of Oracle. My impression, which was confirmed by folks in the Oracle world, is that she knows her way around the Oracle optimizer.

These are my notes from the session, which include comparisons of how Oracle works (which Maria gave) and how MySQL works (which I researched to figure out the difference, which is why this blog post took a month after the conference to write). Note that I am not an expert on data warehousing in either Oracle or MySQL, so these are more concepts to think about than hard-and-fast advice. In some places, I still have questions, and I am happy to have folks comment and contribute what they know.

One interesting point brought up:
Maria quoted someone (she said the name but I did not grab it) from …