Organizations are searching for solutions that provide the speed, simplicity, flexibility and analytic power needed to modernize their data warehouse.

Earlier this week, IBM released a new technology. IBM Integrated Analytics System seamlessly assimilates Netezza technology into the IBM database family. Over the past few months, as part of the beta testing program, Sirius was able to try out the technology before its release.

Three of Sirius’s data and analytics experts—David Birmingham, Frank Pantaleo and Gary Shaw—summarized four ways IBM Integrated Analytics System improves the analytics experience:

1. Common SQL Engine: A common engine provides portability and consistency of a user’s experience related to SQL commands, but also across configuration, implementation and a wide range of database behaviors.

Db2 BLU, Db2 Warehouse (formally dashDB), Db2 Warehouse on Cloud and IBM Integrated Analytics System will share a common front end and common analytics substrate. Libraries such as INZA Analytics, Fluid Query, and SQL Toolkit are integrated. It also means SQL is functionally portable across implementations, and new feature releases are available to all.

2. Solid State Drives: Read speed has always been the #1 problem in a query. Solid state drives can read data far faster than electro-mechanical drives, with no query serialization due to physical disk seeking. This dramatically improves query turnaround time and query concurrency, with minimal breakdown compared to mechanical drives.

3. Columnar Compression: Most technologies pull entire blocks or rows vs. just choosing columns from rows off disks. But with columnar compression, queries are able to pull only the data they need and leave the rest of the row behind, further reducing data coming off the disk.

Netezza is row-based, but IBM Integrated Analytics System inherits BLU’s columnar capability, meaning queries will search and read columns directly, rather than picking columns from rows.

4. Horizontal Frame Expansion: With IBM Integrated Analytics System, a long-desired elasticity has arrived. The use of Power frames instead of blade servers will allow expansion by adding a frame rather than copying data from smaller to larger frames. Now, all we have to do is shut it down, add the additional space, and then start it back up. The machine automatically rebalances the data. And if the user is on the cloud, it’s even faster and easier.

Sirius can help clients bridge the gaps and move to the new high-performance, optimized and cloud-ready data platform. For more information about IBM Integrated Analytics System, download the solution brief. You can also visit for more information, or contact us to request a complimentary demonstration of IBM Integrated Analytics System.