SQL Server 2005 is dead; Long live SQL Server

By Charles

April 6, 2016

SQL, sql 2005, sql server

On 12th April 2016, support for SQL 2005 ended.

What does this mean exactly?

Microsoft is saying if it’s broken, don’t call us. It has been over a decade since the release of SQL Server 2005, and as all good things must end, Microsoft has announced much support for SQL Server 2005.

History will show that SQL Server 2005 was a massive step forward from SQL 2000, the previous version. It set records, improved security and came with the new DTS replacement called SSIS.

Should you move away from SQL Server 2005?

SQL 2005 was the first production version of SQL I worked with, so there is a bit of sadness as I write this, although the longer you work with databases, the older versions you seem to find hidden under desks and forgotten in server rooms.

Five years ago, no one knew about the cloud, and today, your SQL Server can connect and failover into it at the click of a button.

Today’s latest features provide more power and flexibility than ever, allowing some exciting new applications to be written.

If you are still using SQL 2005, and many still are, it is your absolute last chance to move away from it (before support ends) to SQL 2014 or the soon-to-be-released SQL 2016, which both offer much better data analytic options such as improved SSIS, SSRS and SSAS versions and features.

Hopefully, you have already moved away from SQL 2005, but if you have not, it is time to take a step into the present.

If you have an instance or a few of SQL 2005 and you need some help migrating to a later version of SQL Server, need help re-writing SSIS packages and SSRS reports or want to know what the latest SQL Server versions offer, contact us – it’s what we like to discuss the most.


About the author

Microsoft Certified SQL Server DBA with over a decades experience including work for large FTSE 250 companies amongst others. The SQL Server stack has been the focus of almost all of my career in IT. I have experience designing, supporting and troubleshooting large Data Platform deployments.

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