IBM Netezza Performance Server Reviews

• Distributed querying
• Seamless concurrency
• Fast loading
• High velocity analytics

We now have a single store of critical business metrics in the investment bank.

The query optimization is crap, and the machine could use more alerting around bad design and bad queries.

I've been using it for four and a half years.

Releases from IBM are poorly tested, but once they work once, they’re stable – i.e., the machine only goes down immediately after an upgrade.

Scalability is fixed. It’s big, but not at all scalable.

Moderate. IBM is really good at communicating to us that they take our problems seriously, but they don’t seem to fix them very quickly.

We were saddled with this.

The setup was straightforward.

We implemented it in house. My advice would be to follow the tool, and not try to force a schema designed for another system on it.

We have no ROI. We’re a cost center.

No other options were looked at.

It can run heavy CPU queries really fast, and this is valuable.

We have a lot of “campaign” queries that run for our clinical analytical area and this product seems to work well for them.

While some queries do run very fast, you cannot load up the box with several queries.

We've used TwinFin for over four years and Striper for around one-and-a-half.

It does not scale like other databases and expect them to run at the same time.

Netezza does not scale like other databases, so it cannot run several queries at once.

It's good.

It was pretty straightforward, but we had to get several areas involved in initial setup.

We worked with the vendor to implement it.

It is a pretty expensive solution, but it is worth it for the right environment.

In that occasion, the customer was one of the biggest retail companies of Brazil. The company uses SAP and other technologies to manage their transactional process but they didn't have an efficient way to process data and a better view about their business.

The appliance Netezza gave us the capability of process terabytes of data and gave us new directions and ideas to make the business more profitable. We are now able to analyze products, stores, suppliers and sales as quickly as we need to take a decision to handle any kind of issue or prevent loss of sales.

• Easy Deployment
• No Indexes
• Extremely fast to respond queries with high amount of data
• Data distribution based on hashtable concept
• Zonemap
• Easy to migrate data

Concurrent Queries, with this model (1000-3), we had a very big problem using front-end tools connected on it. When using a dashboard tool to use data directly from the database, I had a big problem with queries being queued and stopped running. Looking at the manual I read that Netezza has a limited number or concurrent process.

For 5 years, I was the data architect responsible for the design, the implementation and optimization of all process related to it.

No, I haven´t found any issues.

Yes. If the Demand for clock or disk space grow over the limit, it will be necessary to change the appliance, because it's not possible to upgrade any component of this machine. You have to buy a new one with a bigger capacity.

Customer Service:

6/10 – Some issues about this equipment I had to discover by myself. I think that the vendor did not give me the best support to use the appliance. The machine is excellent, but I had to discover everything by myself as well figure out how to use the equipment in the best way.

Technical Support:

6/10 – I don't know if it is related to the SLA of my customer, but I think that the things are not as fast as they should be when we need help.

I used to have Oracle as my Data Warehouse solution, but despite the fact of it is very good to manage transactional environments, it does not work as fast as Netezza. We have analytical demands so we need an analytical solution. Sometimes we need to retrieve and process our whole table of inventory so it means around 16 billion of rows. Netezza can process all this amount of data and give a result in less than 40 seconds. I have never seen this performance in another database solution before.

The setup was not complex. It was fine. Initially the vendor gave us all the support, including a hands-on course before using the machine.

We implemented by ourselves, my team and I implemented everything.

I do not have this information.

I am not able to give this information.

Yes, I evaluated Teradata and Exadata. Initially I thought that Teradata would be better, so my customer was not able to afford the costs. Now I am sure they made a good choice.

Try to find someone who had already worked with this appliance to have some tips and advices to help you to use it as better as it can. I take too long to discover the best way to make it work well. With my team, I have created a data environment using Netezza as Data warehouse solution, ODI to run the ETL process, shell script. We have now five years of data stored in the Netezza database and we distribute data to all BI Applications easily and quickly. However, it would be better if we had some useful help in the past.

• The ability to load data very quickly
• SQL is 100% ANSI compliant
• Queries run very fast and require no hints (Oracle)
• No space management
• Tuning SQL is generally pretty easy

For every organization that I have been in that has Netezza, the ability to load and run queries is greatly simplified and A LOT faster than any other DBMS out there.

Netezza is just starting on real time integration with Big Insights (big data). Support for interfaces has been poor. Hoping this improves.

I've used it for nine years.

No issues encountered.

Netezza servers used to have disk issues in the early days, however, for the most part this has been addressed.

No issues encountered.

9/10.

9/10.

I have used Oracle and Teradata as a DBA. I have found Netezza to be the easiest in terms of DBA management

Very straightforward. Data movement is very easy. It works better if you do 1 large file as opposed to several small files

Netezza servers are installed by IBM but implementations are sometimes handled in house and for others it maybe a mixture with BI vendors. We are a BI vendor and do implementations.

Most shops I am in have used Oracle, Sql Server, or Teradata. Depending on what the data is being used for (OLTP, OLAP). OLAP is the best application for a Netezza server.

I am using IBM Netezza Performance Server for enterprise data.

The most valuable features of the IBM Netezza Performance Server are the NPS server because of the reduced maintenance and overall good performance.

IBM Netezza Performance Server could improve its interface, support for big data, and APA-based connectivity should be available.

I have been using IBM Netezza Performance Server for approximately seven years.

IBM Netezza Performance Server has a very good uptime rate. We do not have a lot of servers crashing, it is a high-availability solution. 

The scalability of the IBM Netezza Performance Server is good.

We have more than 5,000 users using IBM Netezza Performance Server indirectly. We use BI tools, such as Oracle OBIEE vs QlikView which we use to develop reports and these tools connect to IBM Netezza Performance Server.

I have not contacted the support from IBM. However, our team has connected them.

We used a third party to do the implementation of the solution. There were approximately 25 people for the operation and it took approximately eight months.

We have two people who do the maintenance for IBM Netezza Performance Server.

I rate IBM Netezza Performance Server a seven out of ten.

Our prime use is for warehousing and analytics.

Being an appliance, the best features are its analytics and the performance level.

The underlying hardware that IBM provides with this appliance is made for a specific purpose, to serve performance on a large amount of data, and to do analytics as well. It is faster, when you compare it to any other product, like Hadoop or DXC Hadoop or Presto on AWS. It's made for a specific purpose and it serves that very appropriately.

It really serves its purpose. It meets the need for performance, it meets the need for robustness, and it also serves as a perfect data warehousing appliance. The only issue is that it's not expandable.

The new versions of Netezza, they are expandable. They can be on-prem and on the cloud like dashDB from IBM. It replaces the previous Netezza versions. We are currently on Mako because TwinFin support is going in 2019. Maybe in the next couple of years, we will be replacing Netezza with Redshift.

As a database administrator, and in warehousing part for the last 12 years, we always have stability issues in every technology. So the issue is how well they support their product. IBM does support their product very well. We have had issues where there were queries that were generating billions of rows. It's all about how you understand the underlying architecture. The coder who understands the architecture can write a better query. We sometimes need to educate them. So there are always stability issues but not in terms of hardware or support. It's always how well you write your queries.

If you don't know Netezza, if you don't SQL or you don't know the underlying architecture but you are a good SQL developer, you know all the business logic and you write a query - but it is not actually performing - it's because you have not understood the distribution part of it. You need to consider the distribution keys or the organization keys. That makes the difference.

The stability doesn't depend on the hardware, it depends on your coding in SQL.

If I was using TwinFin appliances, if my data grew to the limit that TwinFin supports, obviously I would have to buy a new appliance. I cannot just ask them to increase the memory or increase the storage or the CPUs. That would cost me another appliance. If our business side agreed to that, I would keep using Netezza and buy a bigger appliance, I'm okay with that. But the expandability is not there.

I would rate the technical support at seven out of 10. We have our own SLAs and they have their own SLAs and things go around that. If we want to a fix in two days, it might be that they are not able to provide it, until it becomes business critical.

Netezza was the first one which we incorporated and started using heavily. Before that, we did test the other data warehousing technology but it was just a PoC and PoV test.

In some of our business areas, they still use SQL Server data warehouses and Oracle data warehouses. But once we moved to Netezza, different business units bought in, and now we are up to Hadoop solutions and AWS solutions.

Once it has been shipped and installed in your data center, it's just the point of plugging it in and the initial configuration. IBM people come and when they install it, they initialize it and then they give us the password and from there we move on in. It's very simple from there.

Netezza is a costly solution. It does serve a specific purpose but it's costlier than what's available in the market, if you go to the cloud.

We are also doing a proof of value and proof of concept for AWS and Hadoop DXC.

My client is looking towards replacing Neteeza with one of the up and coming warehousing solutions like Presto. They don't want the in-house or on-prem cost of managing that particular appliance. When everything is available on cloud, we pay less. My client develops medical products. They wanted to concentrate on the medical part, not on how to manage their IT. So they're moving towards more and more towards the cloud to replace the on-prem solution.

My advice would be to fully categorize your needs. Why you need Netezza should be a specific question, because there are so many different analytic solutions and which provide performance and which are cheaper than Netezza. Until you figure out completely that you only need a PDA (pure data analytics) system, you should really look at other products and compare them.

I wouldn't choose Netezza in today's world when we have Redshift, Presto, EMR, when we have Teradata, and when we have Oracle Autonomous. In today's world, you should look at these solutions first. If they don't serve your purpose, then look to Netezza.

In the current world, data is the big question. Nowadays, we are receiving a lot of data. It's like the data generation has come. We have terabytes of data and it might be, in a year or so, you cross the petabyte scale. So go with a petabyte-scale solution instead of a non-expandable Netezza appliance.

We are currently working on the latest Mako version. After that - Mako retires in 2024 - I don't think they have anything on Netezza. What they have is dashDB and Sailfish, which is a completely different product for IBM, but similar to Netezza. And those are expandable.

Netezza is a good product in and of itself, aside from the fact it is not expandable. Overall, it's a good product but definitely has room for improvement.

IBM PureSystems or NPS has a patented NDAC or Netezza data accelerator card inside each of the SPUs (Snippet Processing Arrays). The SPUs act as individual processors that share part of a query. This helps in high-speed parallel processing of big data volumes. Querying a large data volume takes just a few seconds to minutes, if it is done right.

Analyzing years of data requires high processing power and storage. IBM PDA has exactly that. Years of processed data (tables) can be queried and retrieved based on management requirements. This can be done in minutes for analysis. This is extremely important in identifying trends for decision making in higher management, to serve customers better in today’s business environment.

It is a highly complicated architecture and only IBM engineers/support, or someone who worked on the hardware side of the system, can understand the system architecture completely.

This means that:

• Replacements can only be done by an IBM engineer
• Components are not generic and are not on the market
• Many of the systems are IBM patented
• Service support costs are high

Storage, although high, is limited depending on the rack configuration. For example, an N3001-80, which is an eight-rack Mako Server and also the top end model with the highest storage, can store a maximum of 384TB. Should your data exceed this limit, the storage cannot be extended.

It cannot be used for unprocessed data. The data has to be in a table format.

We have been using the solution for five years.

We rarely had stability issues. You may expect an average of one outage every two months for a few minutes, if it is maintained properly. This is mostly due to “pollreplytimeout” errors of the SPU.

All the rack components are dual for redundancy. Almost all components have failsafe/backup, including the host that is configured in cluster for high availability. With this, the system is up and running all the time, or you can get it up at the earliest possible time in case of component failures/system down situations.

We had scalability issues. Storage, although high, is limited depending on the rack configuration. For example, an N3001-80, which is an eight-rack Mako Server and also the top end model with the highest storage capacity, can store a maximum of 384TB. Should your data exceed this limit, the storage cannot be extended. You will have to purchase a new appliance.

I would rate the technical support at 7/10.

We did not use a previous solution.

IBM sets up the NPS and does the initial configurations. As an admin, you will have a completely configured system ready to work on.

This is a multi-million dollar product. The software and hardware are both IBM patented.

Netezza SQL ('nzsql') runs only on PDA systems, and cannot be installed on other enterprise-class servers. Power consumption is high and these systems must have mandatory IBM support, due to the patented and exclusive IBM hardware. However, the benefits outweigh the costs if you have large data volumes that require fast analysis on a day-to-day basis.

We didn't really examine any alternatives. I started working directly on IBM PDA (Netezza) and I haven't had any chance to work on the competitors' products. I was not a decision maker in the selection of this product. This was a higher management decision.

A close competitor of IBM PDA is Apache Hadoop. As of now, no other product is as fast or as stable.

You can definitely consider this appliance if you have:

• A large volume of processed data (tables) that are created on a daily basis
• Data that requires daily analysis, critical for decision making, and a budget to complement it.

This is one of the most stable and fastest data warehouse appliances available in the market today.

• Zonemap features
• AMPP (SMP+MPP ) architecture
• High availability
• Field-Programmable Gate Arrays (FPGAs)

The Netezza deployment is easy, and there is less administration and coding than in other databases.

• Correlated queries are not supported.
• Concurrency - the performance dips with number of concurrent queries; for example, if more than 48 queries are run concurrently, it queues up.
• Scalability - if the data increases, you need to go for a bigger appliance as you cannot add to Netezza incrementally.

I've used it for two-and-a-half years.

Some minor SPU communication issues with IP protocol.

No issues encountered.

No issues encountered.

They deliver the products to customers faster and with greater accuracy, i.e. within the agreed-upon due date.

Netezza already had a excellent customer satisfaction and the rating would be 8/10.

We previously used Oracle then migrated to Netezza because its deployment is easy, and there is less administration and coding when compared to Oracle. Also, the query performance is excellent in Netezza.

It is very straightforward because Netezza's initial setup took less than two days and the entire data set was loaded onto the Netezza appliance to which users had full access to the system.

Netezza is an easy-to-use data warehouse appliance. It's extremely fast with a low cost and the customers run their BI and advanced analytics in a very flexible manner.

We also looked at Teradata.

Netezza should have enough advantages with implementation, i.e time to deployment, price, performance, and the ability to integrate with the existing environment.