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Displaying posts with tag: Microsoft SQL Server (reset)
Log Buffer #482: A Carnival of the Vanities for DBAs

This Week’s log buffer edition covers some of the useful blog posts from Oracle, SQL Server and MySQL.

Oracle:

ASM disks – lsdg compared with the v$asm_diskgroup view

Can a query on the standby update the primary ?

What should I know about SQL?

Setting Environment Variables in Application Server/Process Scheduler Tuxedo Domains

Oracle …

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Amazon RDS Migration Tool

Amazon has just released their RDS Migration Tool, and Pythian has recently undertaken training to use for our clients. I wanted to share my initial thoughts on the tool, give some background on its internals, and provide a walk-through on the functionality it will be most commonly used for.

There are many factors to consider when evaluating cloud service providers, including cost, performance, and high availability and disaster recovery options. One of the most critical and overlooked elements of any cloud offering though, is the ease of migration. Often, weeks are spent evaluating all of the options only to discover after the choice is made that it will take hours of expensive downtime to complete the migration, and that there is no good rollback option in the case of failure.

In order to reduce the friction inherent in the move to a DBaaS offering, Amazon has developed an RDS Migration tool. This is an in-depth look at this new …

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Log Buffer #348, A Carnival of the Vanities for DBAs

With the holiday season fast approaching (or is it slow?), data bloggers have already adopted a festive mood, and this Log Buffer edition jubilantly captures and reflects that, and much more.

Oracle:

On December 4, 2013, Oracle will host a customer webcast to acquaint customers with the Oracle SuperCluster M6-32, Oracle’s most powerful engineered system for in-memory Oracle Database performance, Database-as-a-Service and application consolidation.

The ETL logic in BI Apps uses parameters in packages, interfaces, load plans, and knowledge modules (KM) to control the ETL behaviors.

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Webinar: NoSQL, NewSQL, Hadoop and the future of Big Data management

Join me for a webinar where I discuss how the recent changes and trends in big data management effect the enterprise.  This event is sponsored by Red Rock and RockSolid.

Overview:

It is an exciting and interesting time to be involved in data. More change of influence has occurred in the database management in the last 18 months than has occurred in the last 18 years. New technologies such as NoSQL & Hadoop and radical redesigns of existing technologies, like NewSQL , will change dramatically how we manage data moving forward. 

These technologies bring with them possibilities both in terms of the scale of data retained but also in how this data can be utilized as an information asset. The ability to leverage Big Data to …

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What is the biggest challenge for Big Data?

Often I think about challenges that organizations face with “Big Data”.  While Big Data is a generic and over used term, what I am really referring to is an organizations ability to disseminate, understand and ultimately benefit from increasing volumes of data.  It is almost without question that in the future customers will be won/lost, competitive advantage will be gained/forfeited and businesses will succeed/fail based on their ability to leverage their data assets.

It may be surprising what I think are the near term challenges.  Largely I don’t think these are purely technical.  There are enough wheels in motion now to almost guarantee that data accessibility will continue to improve at pace in-line with the increase in data volume.  Sure, there will continue to be lots of interesting innovation with technology, but when organizations like …

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Reply to The Future of the NoSQL, SQL, and RDBMS Markets

Conor O'Mahony over at IBM wrote a good post on a favorite topic of mine “The Future of the NoSQL, SQL, and RDBMS Markets”.  If this is of interest to you then I suggest you read his original post.  I replied in the comments but thought I would also repost my reply here.

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Hi Connor, I wish it was as simple as SQL & RDBMS is good for this and NoSQL is good for that.  For me at least, the waters are much muddier than that.

The benefit of SQL & RDBMS is that its general purpose nature has meant it can be applied to a lot of problems, and because of its …

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IA Ventures - Jobs shout out

My friends over at IA Ventures are looking both for an Analyst and for an Associate to their team.  If Big Data, New York and start-ups is in your blood then I can’t think of a better VC to be involved in. 

From the IA blog:

"IA Ventures funds early-stage Big Data companies creating competitive advantage through data and we’re looking for two start-up junkies to join our team – one full-time associate / community manager and one full time analyst. Because there are only four of us (we’re a start-up ourselves, in fact), we’ll need you to help us investigate companies, learn about industries, develop investment theses, perform internal operations, organize community events, and work with portfolio companies—basically, you can take on as much …

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What Scales Best?

It is a constant, yet interesting debate in the world of big data.  What scales best?  OldSQL, NoSQL, NewSQL?

I have a longer post coming on this soon.  But for now, let me make the following comments.  Generally, most data technologies can be made to scale - somehow.  Scaling up tends not to be too much of an issue, scaling out is where the difficulties begin.  Yet, most data technologies can be scaled in one form or another to meet a data challenge even if the result isn’t pretty. 

What is best?  Well that comes down to the resulting complexity, cost, performance and other trade-offs.  Trade-offs are key as there are almost always significant concessions to be made as you scale up.

A recent example of mine, I was looking at scalability aspects of MySQL.  In particular, MySQL Cluster.  It is …

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Who/What to acquire next

Well as predicted, with Aster Data recently being picked up by Teradata most of the key new generation MPP distributed analytics vendors have been acquired (Aster Data, Vertica, Netezza & Greenplum).  This had to happen and was expected to happen.  The MPP Analytics startup “revolution” is over and these technologies will now be integrated into the mainstream.

So what’s next?  As we now, if you are a massive multi-national software company it is a lot less risky to incrementally innovate and leave the development of “game changing” technologies to startups that can be acquired after they prove both the tech and the market.  So what follows MPP? …

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The problem with a full box of big data tools

NoSQL”, for lack of better name, is a generic term that describes any data management system that does not use SQL as a query interface.  Generally this means any data management system that is non-relational, but the term also has also been stretched as far to include the boundaries of what constitutes a data management system at all (such as Hadoop).

Early on (a couple of years back in NoSQL time) when the term was coined I think the positioning was much more aggressive, but more recently this has been softened so now NoSQL is commonly quoted as meaning of “Not only SQL” or “next generation databases” (whatever that means).  The common message you get now is something along the lines of NoSQL systems are more “specialized”, each being designed to solve a smaller number of problems than the …

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