Netezza Analytics Reviews

There is minimal on-going maintenance.

There were some reports we couldn't get because of performance, but with Netezza we could get more of them.

It needs a better in-house development tool.

I've used it for three years.

Functions are difficult to deploy.

No issues encountered.

No issues encountered.

7/10.

7/10.

Our customers mostly switch from traditional RDMs to appliances.

It is very easy to setup.

We used an in-house vendor who were 8/10.

Choose your most complex scenario. Do a POC and try to scale.

You should know how it works well so you can use its power. So, start with a partner or vendor team.

ARULES() function is the fastest implementation of the associations algorithm (a priori or tree) I have worked with. In comparison with the R associations package, it is +1000x faster. The issue with the R implementation, and R in general, is that the functions do not work on large sets of data. R would generate a 100,000 x 100,000 element matrix for some of the arules runs we do – very, very inefficient programming.

Any in db machine, learning functions help by eliminating the data transport issue. NZA goes one better by allowing you to utilize a tuned engine (software + hardware) to run the functions. The result is that we can run algorithms that would be impossible to run on other platforms.

We are using an older version. Some improvements are already implemented, such as the addition of neural networks. Other improvement would be to make the existing algorithms even faster, e.g. kmeans can actually be parallelized. If this reworking of the algorithm is done, it should leverage the MPP architecture of Netzza and run much faster.

Also, some algorithms are faster than almost any other method or system e.g. NZA.ARULES() function. Whereas others are not as fast and could probably be optimized for an MPP architecture like kmeans function.

2-3 years on and off. 1 year for actual integration into another tool for mass consumption.

For deployment, ensure you follow the instructions. The version of Netezza must be matched with the version of NZA. We tried to install a newer version of NZA not supported by the version of Netezza we had and it did not work.

N/A. We did not engage IBM tech support, mainly due to past experiences where it is faster, easier and much less stressful to just figure things out yourself.

Rapidminer, R, DB2 intelligent miner, SSAS data mining were all tested for association rules. Rapidminer and R did not pass. They use matrix math, and cause +100x performance degradations. DB2 intelligent miner, SSAS data mining, and likely also NZA follows the original a prori methods of using sets, not matrices.

DBA set it up, but it seemed very simple. I helped with designing the overall architecture. If you stick with NZA as a “function repository DB” concept and do not put data on it (as recommended in the install manual) you will be ok.

In-house. Don’t over think it. Just apply some base architectural principals and give it a try. If you find something not working make adjustments.

I had nNo visibility to pricing. Netezza in general though, is very cost effective. If you compare to other MPP platforms like Hadoop. Hadoop requires a very “non-enterprise” culture to implement and a team of designers / engineers. Netezza requires maybe 1-2 admins.

I would have to understand the specifics of the organization, the data size, the tasks, etc. to make any recommendations.

Its query performance and speed.

Earlier there was high latency to query extraction but Netezza has improved the speed for all OLAP operations. This has helped the organization to get the business answers right on time.

• Matching up with big data.
• Netezza has been built only for OLAP and structured data, and I think IBM must do something to match it to Hadoop scalability.

I've used it for four years.

There’s only been one, where data slices were corrupted soon after the deployment but IBM has fixed it in a perfect manner.

No issues encountered.

We didn’t have many scalability issues, except when it touches the PB storage data and we need to move it to external storage. Netezzas’ highest model storage capacity is 1.2 PB.

Great, 8/10.

Great, 8/10.

We have previously used Microsoft SQL server, but we switched because our business wants fast and reliable appliance like Netezza. Although MS SQL server is reliable but Netezza is known for it's MPP and performance when compared to other RDBMS appliances.

Straightforward.

An IBM team deployed it for us, and they were 9/10.

Business questions are answered much quicker than what we use to do it earlier.

The Netezza appliance is bit costly for a mid-sized organization but highly effective on the performance side and for structured data.

We also looked at Oracle and SQL Server.

I don’t want to be biased but it all depends on the business requirement because there are many models for it, which range from 7.8 TB to 1.2 PB (uncompressed). If the business has done a feasibility check on Netezza for their scalability plus the growth and they found it to be within their estimates then I would suggest that they have taken off from the right runway.