Last week, we had the first CTP of SQL Server 2008 R2 become available for download.
What probably didn’t get as much air time (although I’m sure many of you know about it) is that we’ve also released a couple of related CTP’s that you might be interested in.
First up we released SQL Server 2008 project “Madison” in CTP form about a week ago. Project Madison is the high end Data Warehouse offering that integrates the recently acquired DATAllegro product with SQL Server. This is not a public CTP, but if you are interested in getting more information on this technology preview, please let me know and we’ll see what we can do to help you out. Note that there are fairly hefty requirements (from a deployment perspective) that you’ll need to manage, but in exchange we can likely help with some pre-release support.
Also, from a couple of days ago there is a CTP of SQL Server StreamInsight available fro TechNet and MSDN subscribers. StreamInsight is a high performance process intelligence tool which allows you to build applications that handle streams of data as it flows through the organization (e.g. from the likes of BizTalk Server). As the data comes through SteamInsight has the tools to help you find patterns in your data streams and then make business or process based decisions based on these patterns. This allows businesses to make decisions about data in near real-time in scenarios where event based information is critical to the decision making process. More information about this feature of SQL 2008 R2 is here.
Finally, if you’ve been thinking of putting your data in the cloud
, the SQL Azure CTP is also now available. The team have made some significant changes since this was announced at PDC last year, so I’m looking forward to seeing what’s in it. If you are heading to Tech Ed, NZ make sure you head along to the very excellent Mr Jeremy Boyd’s session on SQL Azure – its sure to be a good session. You can sign up for the SQL Azure CTP here and you can get more information on it here.
These last two announcements were made on the Data Platform Insider blog.