SQL SERVER – Few Notes on Fast Track Data Warehouse

I recently delivered fast track data warehouse training. This training was very challenging as this training requires very specific hardware and extremely different way of looking at data warehousing. While training I have made few notes and I will now share the same notes with you. Please note that this are just notes and not learning material.

SQL SERVER - Few Notes on Fast Track Data Warehouse fast-track-DW

  • Fast Track Data Warehouse has a primary emphasis on eliminating potential performance bottlenecks.
  • It supports maximum of 48 TB data at this moment.
  • Currently HP, Dell, Bull, IBM and EMC2 provides necessary hardware for Fast Track Data Warehouse.
  • All the Software and Hardware comes in a single package.
  • The Base OS is Windows Server 2008 and Base Database is SQL Server 2008 R2.
  • FTRA stands for Fast Track Reference Architecture.
  • SMP stands for Symmetric Multiprocessing.
  • Fast Track is pre-configured and it just works out of the box.
  • PDW stands for Parallel Data Warehouse.
  • Fast Track Data Warehouse is based on Symmetrical Multi Processing (SMP) and PDW is based on Massively Parallel Processing (MPP).
  • Each CPU Core delivers 200 MB per second data.
  • This hardware architecture is available at $13,000 per Terabyte.
  • It uses RAID 1 Mirror sets
  • Recovery model of FTDW is recommended to Simple Recovery mode.
  • Turn off AutoGrow for user defined database.
  • Leave AutoGrow On for TempDB and set at 4 MB.
  • Update the database statistics regularly.

I really had great time doing training for this subject. If you have worked with Fast Track Data Warehouse, what was your experience?

Reference: Pinal Dave (https://blog.sqlauthority.com)

Data Warehousing
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2 Comments. Leave new

  • Wonderful I have been searching for FTRA information for some time now because I am in the process of upgrading a huge DWH, your information will honestly aid me very well, thanks for sharing.

  • Thanks for the info pinal on Fast Track Data Warehouse.


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