IBM Netezza Performance Server Pros and Cons

High through put. On the fly fact calculation is very robust and returns data on huge amounts of data quickly. This helps us create and report facts directly from dis-aggregated data on the fly.

We are handling heavy volume of transaction data and pre-aggregating the facts would be prohibitively costly and almost impossible to do. Having the capability to do mass data operations on the fly is very helpful for our organization. Review collected by and hosted on G2.com.

The max size a Netezza box can handle is pre-determined by the configuration. Meaning, it is not infinitely scalable.

Cost of the servers are too big for a small size firm. Review collected by and hosted on G2.com.

If you are looking for database with high storage and parallely high performance then Netezza is best for that . Netezza is usefull for data warehouse appliances and advanced analytics applications for uses including enterprise data warehousing, business intelligence, predictive analytics and business continuity planning.

Quick Technical Support Team of IBM Review collected by and hosted on G2.com.

You need to know better and best way to design your database . How to use organize key and distribution key to make it better and best . There is nothing in it to dislike it . One suggestion i want to give to IBM Team that make NZadmin more better than other .... Review collected by and hosted on G2.com.

Not having too much experience with other BI/DW solutions, I like that the administration of the appliance is so simple. From a design perspective, I like that there is careful consideration in obfuscating the physical and logical elements of the appliance. Review collected by and hosted on G2.com.

My oganization has invested millions in the procurement of Netezza appliances when Netezza was its own company. Not to put IBM at fault here but with security being a mainstream focus, I was not thrilled to the idea of any organization acquiring new hardware to benefit from hardware encryption. Personally, I think there should be some legacy support to not only have a softwrae based encryption solution. Review collected by and hosted on G2.com.

The raw speed of the system allows for a development process not typically undertaken. For example, it's possible to run full performance testing as you unit test. You can also create tables that are much larger than you would make in a typical database (eg storing current and archive rows in the same tables).

The simplicity of the system allows for minimal maintenance. DBA involvement can be next to zero. Review collected by and hosted on G2.com.

The simplicity of the system can also cause issues in mixed use cases.

In other databases, you also have the ability to improve performance by multiple means, such as partitioning, indexing, allocating server hardware, etc. Netezza essentially has only two ways--as far as physical architecture goes--to handle performance: sorting data and distributing data.

Sorting data is done directly in the table, avoiding the need for clustered indexes. But that's only helpful if the query you run utilizes that sort. For instance, if you sort on date by making the Date field the ORGANIZE BY key, any query that doesn't utilize Date in the WHERE clause will have to tablescan. You can create materialized views that essentially act like indexes, but you can't use both MVs and ORGANIZE BY keys. In other words, if you use even one MV to sort, you can't force-sort the data in the table unless you actually reload the data with an ORDER BY clause in the INSERT statement. The problem with the MVs is that even though they act like an index, you have to refresh them like a typical MV in order to sort any new data. In a system that is loaded or updated intraday, that can cause problems.

Distribution has two components that can sometimes be at odds with each other: evenly hashing the data to share workload and colocating data for joins. But if the column that makes sense to distribute on for colocation purposes doesn't evenly distribute the data, you will be forced to make a compromise on one for the sake of the other.

Furthermore, in a star schema, you can colocate the fact table's foreign key with a dimension's primary key, but that is best used if you query with a parameter on that dimension in the WHERE clause. If you run a query that can't filter on that dimension, the distribution key might not help you. Also, you can only ever pick one dimension to colocate with the fact. Choosing a multi-column distribution of the fact based on multiple dimension keys does not colocate the fact with _each_ dimension. It instead distributes the fact with a hash key based on the concatenated combination of the values of the multi-column distribution key (ie the fact will not be colocated with _any_ dimension).

Also, the fact that Netezza has not come out with in-memory or columnar options makes me wonder if the architecture of the appliance even allows for such possibilities. In other words, the lack of flexibility might be cropping up again if the nature of the appliance doesn't allow for such varied functionality. Review collected by and hosted on G2.com.

First of all, Netezza requires minimum DBA administration. It means it can maintain with less sys and dba resources.

Second, it has nothing share disk resource nothing like Oracle shared storage. It has own architecture and algorithm to move data. And it is not using index at all. So called "Zone mapping" it help a lot for heavy query from the BI users. Review collected by and hosted on G2.com.

Our company Netezza was not actually built for real time replication. I have to spend a lot of time to fix this issue so called CDC. Review collected by and hosted on G2.com.

This is a great data warehouse appliance if you want to keep things simple and solve data problems that require scale. Review collected by and hosted on G2.com.

Too many hardware outages (albeit hot swappable) causing constant request to IBM support. Review collected by and hosted on G2.com.

Blazingly fast for Queries.

Very little maintenance, hence needs minimal support from DBA. Review collected by and hosted on G2.com.

Concurrency - performance dips with number of concurrent queries. If more than 48 queries concurrently, it ques up.

Scalability - If your data increases, you need to go for a bigger appliance. Cannot add incrementally

Backup and Replication :-(

Some kinds of Correlated Queries not supported Review collected by and hosted on G2.com.

As a data warehouse architect I built star schema data mart in netezza.I liked the netezza parallel architecture which helped processing multi terabytes of data at lightning speed. Review collected by and hosted on G2.com.

There is nothing much to dislike. But it would be great if netezza improves its performance monitoring and alerting system. Review collected by and hosted on G2.com.

Immense time to value

Low administrative costs

Great hardware compression capabilities

Scalability Review collected by and hosted on G2.com.

Load utility not as fast as competition

Large overhead for conversions from an existing implementation to Netezza (largely due to lack of indexes) Review collected by and hosted on G2.com.

I have been using netezza since three years , I have worked extensively in twinfin, striper and now in mako. I can definitely say it's the best analytical query processing I have every seen. This is a good candidate to meet or beat mainframe processing speed in terms of batch processing. Review collected by and hosted on G2.com.

Waiting how they are going to handle big data Review collected by and hosted on G2.com.