Uncovering the truth about more outrageous competitor claims

Another of the claims this competitor made is that Netezza cannot handle the data ingest from a point of sale (POS) type system because so it could not handle the data being sent from the hundreds or thousands of POS systems at the same time. They go on to claim that Netezza cannot handle more than a specific, ridiculously small, number of concurrent writes to try to give credence to this argument.

In my opinion, this point shows a lack of knowledge of real data warehousing and analytics. IBM Netezza has a large number of retail customers who feed their POS data into Netezza all the time. But, this data normally always comes into the data center in some non-database type of communication protocol. The data is then extracted from these POS feeds, and has meta data management and identity assertion algorithms applied against it, because the data may be coming from many different stores, even different “named” stores where the same item may have different SKUs. Only then is the cleansed data loaded into the warehouse, it is not loaded directly from the hundreds/thousands of POS applications/registers.

IBM Netezza absolutely supports trickle feed and real/near-real time updates from this type of data stream process, as well as direct replication from other relational databases.

And, if you are looking for the ultimate in real time reporting and analytics on your POS data, IBM has the system for you. The IBM DB2 Analytics Accelerator is an IBM Netezza system connected directly to a DB2 for z/OS system using the zEnterprise connection. In this configuration, the transactional applications still run against the tried and true DB2 for z/OS system, and reporting/analytic queries get transparently routed through the DB2 for z/OS system to the Netezza system, to offload the processing and resource usage, and ultimately run much faster. DB2 for z/OS systems run many of the world’s largest scale OLTP applications, and this brings them the power of real time analytics without the need to create extra indexes, aggregates, etc. in their DB2 for z/OS system which are needed to allow the reports/analytics to run quickly enough, but also have a detrimental effect on the transactional performance.