IBM Netezza Performance Server Reviews

The performance is most important to me, and it helps our ability to make business decisions quickly.

They should make it work better in a multi-user context. This solution works, but not for the workload we have.

It is stable. We use it in our data warehousing complex, and the performance is good.

The scalability is not as expected. It is shipped to you as an appliance, a black box. If you want to expand it, you have to get an extra CD,or whatever, and they come and program something int he box to release extra bits. If this were a cloud product, you could just expand and subtract as you wish. The capacity in this black box is not enough.

I would rate the tech support a five, on a scale of one to ten. It is obviously not that great. 

We had Teradata before, and I am not really sure why we switched.

Based on first conception, do a POC, scale up to the volumes and get the vendor to prove that it can work with their requirements. Get them to scale it up, either simulate it, make sure it can actually do what it says, rather than buying beta and then get it and then find out that it doesn't actually do everything it says it does.

We use it primarily for analytics.

Over 90 percent of our query executions are one second or less. We do millions of queries everyday.

• It is hands-off when everything works well. 
• We are able to execute very complex queries.
• It has good performance.

Our main problem with it is concurrency. When there are too many users running Netezza at the same time, this is when we have the most complaints.

Stability-wise, the product has improved. Netezza has improved the product over the past 10 years. We now have better monitoring and can be more proactive about detecting issues.

We have come to the point where we need to watch out for our capacity, as we are adding more users onboard with Netezza. We are not able to scale. The only way to scale is to get another appliance, but we have a customers who would need us to hydrate the data between the two appliances, and Netezza does not do that.

We are looking at the cloud approach, but we still have applications on-premise that we have to support.

The technical support has degraded overtime, especially after Netezza was bought by IBM. It appears as if some of the Netezza's SMEs left after IBM bought them.

We were previously using Oracle Database. We switched for performance reasons and running complex queries. Compared to Oracle, Netezza has superior performance.

The initial setup was very complex. However, this can be attributed to our environment and the complexity of the business which we process.

The pricing is very expensive. It has a lot CPUs with a lot of components in it. It also has built-in redundancy for resiliency reasons. I believe that's why it is so expensive.

We did look at some other analytics platforms a few years back.

We are now looking at solutions due to scalability, such as: Db2 Warehouse, Exadata, Teradata, and Yellow Brick. Then, on the cloud side, we are considering Redshift and Snowflake.

Get the requirements and have them finalized. Then, be very specific about the requirements that your organization needs. Based upon your requirements:

1. Identify whether Netezza will be suitable for your requirements. 
2. Get the sizing right.

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.

Neteeza is a data warehouse for customer analytics. 

We're looking to get away from it, so I can't really say that it improved things. It did augment some of our product delivery resources.

The most valuable feature would be the fact that it has been running for awhile in an appliance format. The appliance format may be the best part.

There won't be another release. They're converting to DB2 and that is one of the reasons we are looking at other options.

In terms of features that I would like to see, one is the ability to actually scale out an architecture. Right now, if you buy one, it's fixed. There is no scale-up availability at all.

It's pretty good when it works. It's pretty stable overall. But if you have a problem, support is a nightmare.

Scalability is not possible.

Technical support has been awful. I found them unwilling to help, and with direct VPN connection to systems, unwilling to actually connect and look at information, which is part of our contract. They did not actually do their job.

We're looking to switch away from Netezza because the platform database system that it runs on is no longer going to be in existence. It's moving to DB2. If it moves to that direction, the amount of changes in logic and queries that it would require is pretty substantial. At that point I would basically be rewriting everything.

When selecting a vendor, obviously I don't want somebody who is brand new. I want somebody who has a track record of actually being around for awhile. It needs to be a company with a product that does the functions that a database should do, and not something that's only a partial solution. There are a lot of solutions out there that do three-quarters of what a warehouse should be doing, but three-quarters of a warehouse are not sufficient.

I wasn't involved in the setup. But it's an appliance, so there is no real setup, other than there is a day for an IBM technician to come out and stand it up.

Vertica was one of them. I looked at it recently. It has limiting factors on things like updates and deletes of data, where it has performance issues. That's a big problem for us. 

I rate Netezza at four out of 10. There is not too much involved to set one up from a customer perspective, but after the initial setup it is pretty awful on the customer support side of it.

My advice would be, check out all options. Don't just go with big-name vendors, because that is not always going to be the right answer.

For now, we use that as our enterprise-wide data warehouse. Performance-wise, it's been great. The speed has been excellent. We haven't really had any hardware issues with it that I'm aware of. We've had it for heavy-use in the past six months to a year. It's been good.

The big benefit that we've had is, in the past with the legacy data warehouse solution, we've been limited to having just a nightly batch, running on SQL Server. It's a slower batch process, so throughout the day we would be limited to stuff that happened as of some time in the evening. 

So the benefit is really because of the additional speed that we have and, truth be told, the more updated ETL processes and the revamped scheduler in general. We've been able to move the refresh timing up to six times a day, so at any given point in the day, the data would be only four hours old, which helps us give much better - not quite real-time data - but closer to real-time data for the day, which helps the decision-makers get the most up-to-date information possible.

The speed.

I would say it's very stable. Whenever we have any sort of outage, the hardware team always communicates it, and it's been months since we've had any sort of outage, outside of the standard maintenance window. There have never really been any issues there. Stability has been good.

For scalability, we're still in process - half the business is still not on this data warehouse, the company is also moving over to a different production system - so the scalability, we'll really see throughout this year, as the rest of the business gets migrated over to that new production system, and that data will be falling into the Netezza data warehouse platform. So for scalability, it's a little too soon to really give an answer yet.

I have not used tech support. I'm not on the hardware team.

Our IT leadership made the decision to go with Netezza before I joined the company, that decision had already been made. Prior to that we were using Microsoft SQL Server.

The only thing that I was really privy to was, Netezza was chosen because of its analytical capabilities and for the ability to process through a very high volume of records and give an aggregate solution from an analysis standpoint, in a very quick fashion.

I was not involved on the hardware side, but I was on the data modeling aspect.

I would say it was straightforward. We used the IBM InfoSphere for the ETL scripts. Those seem to give plenty of visibility for allthe different steps in the ETL process, especially debugging or going in and making modifications as different tickets come through.

Working with some of the other developers, whenever they are given a ticket, it's pretty simple to see what step in the process and additional code needs to be added, or modified, or removed; to see exactly where it is and how it's going to affect things downstream, and to be able to see at what exact point that something has failed. That part, it's been more straightforward and just the visibility of the whole process.

The most important criteria when selecting a vendor for a data warehouse solution are, obviously, the speed and the ability to handle large amounts of data. That's especially true from an analysis standpoint, and having it not only do the math and select statements but also do more aggregation and analysis-type queries.

The speed has been excellent for us, in pulling information, as well as the batch timing, and the suite of tools that comes with it for the ETL withIBM InfoSphere. Also, the data governance prospect, as a company we haven't really delved too far into that, but from what I've seen, that is a really powerful tool as well, to help with data lineage and keeping track of that. So the speed is good and the suite of tools seems to be very beneficial.

From my standpoint, I would give it a nine out of 10. It has done everything that we needed it to do, it's great. The only reason I wouldn't give it a 10 is because, early on, there were a couple of maintenance things that we had to do.

We use Netezza and Teradata in our project environment where I work as an admin and data modeler.

Distribution concurrency control.

Concurrency limit needs to be increased somewhat.

Great stability in Netazza's Mako.

As of now, no issues with scalability. But like Teradata, we can’t add a node/SPU to the existing appliance.

I work with IBM PDA support. They are wonderful and fix issues in good time.

We used Teradata for Data Mart for certain applications but issues arose once the data setup grew. Using PDA, the issues were resolved.

Setup is not that complex. Within 24 hours we had everything completed and had copied the dataset from Oracle. Our migration approach was to use a shell script (pipe).

Best if you have a robust infrastructure, where network bandwidth is good. We used 10GB Ethernet cable for data transfer.

Enterprise reporting data warehouse using Business Objects, Microstrategy and data mining using SQL. Being a data repository for a single customer view. Also contained staging tables, some of which were designed like an ODS and contained all data from the source system and was updated on a nightly basis. The applicance contained over 12 TB of data uncompressed (less than 4 TB compressed).

Reports which used to take between 30 to 60 minutes or would time out on an Oracle database, which was previously used for the enterprise DWH, now run consistently in seconds or in less than five minutes.

High performance RDBMS appliance optimized for data warehousing and enterprise reporting. Very simple to manage huge volumes of data without having to worry about indexing and partitioning. Automated compression of tables without any custom scripting or manual intervention. Achieved almost 3x compression effortlessly which meant that 12 TB of data compressed into around 4 TB.

Could do better to support more concurrent update queries. We had to stagger our ETL loads to prevent queuing of jobs and random failures.

Also, it would have been good if the admin application showed more detail on the validity and usage of zone maps (this may have been implemented in later versions of the admin app).

The database runs stable unless there are hundreds of queries running in parallel.

Every query is a full table scan. If the table contains mostly integers, then performance is good. If the number of users is in the thousands, then it may be better to use cubes or other solutions to service reporting needs.

Before being acquired by IBM, Netezza corporation had exceptional support and used to respond very quickly (less than 30 minutes) in case of production issues. Round the clock support and monitoring were offered and support tickets were handed over very professionally between engineers working across time zones. After being acquired by IBM, support has not been as responsive, but there weren't as many issues as the box was stable.

Previously, Oracle was used as the data warehousing platform, and performance was low and not meeting the needs of the enterprise reporting and analytic user community. My customer switched to Netezza mainly for performance, and it was a big improvement.

As the box was very heavy, datacenter flooring required additional reinforcement. The box runs Linux and the initial setup is quite straightforward. ODBC drivers on the servers (ETL or reporting) which connect to the box may need to be upgraded.

Implemented this through a vendor team. As there is no need to spend time on partitioning and indexing, a lot of vendor time was saved. Table scripts for partitioned oracle tables run into hundreds or thousands of lines of code and we used to be charged accordingly. But a Netezza table script is much much simpler and we saved money there. Review of table scripts for performance and best practice was also easier as there is only a limited set of best practices to be implemented for high performance. So even vendor teams having low or medium level of expertise can deliver properly as long as they understand how MPP works - governance effort is definitely lesser with Netezza compared to Oracle or SQL Server.

ROI is high because analyst productivity improved drastically. As mentioned before, queries which used to run for several minutes now run in seconds or less than a few minutes or the duration of a typical pop song. So analysts can ask more questions of the data per hour compared to Oracle.

Also, the compression feature saved us a lot of money on per terabyte costs for the data.

From a cost per terabyte perspective, Netezza is definitely more expensive compared to Hive on Hadoop, but due to its simplicity and ANSI SQL Compliance and high performance which can be achieved with less tuning, it may be worth it.

My customer upgraded from Netezza 4.x to Twinfin 6.x.

Netezza is a great option for data warehousing, but give due attention to concurrency and find out how much would be the peak load the database may have to handle. Also, check whether performance is acceptable for APIs and web services. Performance may not scale for thousands of single row lookups, as the database is more suited for complex aggregated data warehousing queries.

Currently, we are using Netezza to the utmost. We first used it for our data warehouse. Then we moved on to doing analytics. Also, we are now doing some packages on it. Currently we are using it for multiple purposes, but, mostly it's used for reporting.

It is a back end for our SSIS, MicroStrategy,, Tableau. All of these are connecting to get the data. To do so we are also using our analytics which is built on the data.

I'm working for a retail client. We have a lot of reports, which are for store managers. The store managers used to get all the reports using the SSIS package, which was built upon our back end and they would have a lot of performance issues. When I say performance issues, in the morning when there are almost 2,000 users trying to connect to the same report, there were a lot of problems because it was a relational database. People were trying to get information out of it and it would break the flow, actually bottleneck the flow. That's why they were getting the impact.

What we did is, we did a PoC and found this client is well built. Because of that, we were able to create a separate layer for reporting. There was a simple requirement for the DBA, where we don't need to build an index or anything like that. Those reports were improved from a couple of hours to minutes. That was the biggest benefit we've had from this appliance.

For me, mainly, it reduces my costs. It's not only the appliance cost. There are also support costs and a maintenance costs. It does reduce the costs very drastically.

Administration of this product is too tough. It's very complex because of the tools which it's missing. We would require better tools for doing administration. For example, if I need to get a permission of a user on a particular object, it is so complex. It's not straightforward. It would not give me a display of that particular element. Basically auditing is tough to do on it. If I don't have a graphical tool, the auditor will ask me thousands of questions.

This is my seventh year.

Stability, no. In production, no. But when we are migrating or we are moving out from one platform to another... but I guess that doesn't count.

It is scalable to multiples of itself. If currently it is 1X, I can go to 3X, 4X, 5X. I cannot go 1.2, 1.5, 1.8. I have to go 1X, 2X, 3X, a whole interval. That is the only catch, otherwise yes, it is scalable.

We were using a different product. We switched it because of the cost of maintenance. We wanted to reduce the cost of maintenance and it helped to drastically reduce it by some 40 to 50%.

I'm not sure what to compare it to. I am a DBA. For me to set it up, it would be a fast setup. If I'm not a DBA, then it would totally take a little bit of time. For someone who is new to Netezza, it's not complex but it requires prerequisite knowledge. That's it.

I would rate the setup as medium complexity, given that we have somebody who knows a little bit of database administration. I would not say the full administration. I would rate setup around two and a half out of five.

We did. We were actually looking at Teradata and Exadata and we chose Netezza.

The first thing is, do a full PoC where you actually plug in dummy data. Start with millions of records and try out the options which you have already in your environment and see if you really get a benefit in terms of performance. Because this product is mainly to improve the performance.

There are two things. First, it improves the performance and then it's easy to maintain. When I say easy, you would not need a DBA at all. Anybody who has really good knowledge in SQL should be able to maintain this product. That cost, of a DBA, you will completely be eliminating.

The first part of this product is basically performance. If you are moving on from an ODBC database to this, then you would need to do a round of testing on data because you are actually moving from a different technology, that is, to an appliance technology. There are multiple things which can stop you, things you might not be able to do; operations, like booking of a ticket or reloading a feed. We tried to do those things here, in Oracle or MySQL, but when it comes to reporting, this is the best solution we have so far. By that I mean, cheapest and the best.

Then, try to figure out if you really require a code change, because there is a minimal time for a code change; but if it's a request then you should catch it when you're doing a PoC.

Take out any complex situation, give it to the vendor, IBM. Tell them to do a small PoC on the dummy data and let them come up with the performance, then you can compare with your feeds.

Overall, it has good connectivity with almost all the niche technologies we have on the market right now. It can scale up to any technology, any content. That is another benefit of having this.

IBM is a good company which always tries to be competitive with other technologies on the market. If we are stuck, we are trying to purchase something for our content and we are stuck somewhere, something is missing, we approach them and these guys will give us the solution in terms of a patch or an API or something like that, which will help us connect to the newest technologies.

• Its ability to process and query large amounts of structured data.
• Low administrative support in terms of query optimization and indexing support. Indexing and data partitioning is built into the firmware.
• Data compression. It was relatively impressive. I think at some point we were getting 4:1 compression if not more.

I can't because we're using it in a fashion such that a traditional RDMS could have been used in place of it. Our data was relatively small so we didn't see a huge benefit in transitioning new subject areas into production.

Community support. There was none, or very little, especially when using add-on software (e.g. building functions, MapReduce, R, Lua, etc.).

Driver support for windows based applications.

Disaster recovery support. Because it was an appliance, and if you wanted to support disaster recovery, you needed to buy two.

Data center moves. The TwinFin was cool to look at, but moving was a huge orchestration. I would definitely go cloud if I was to choose something with this type of processing power.

Four years.

Yes, with drivers, either OLE DB or ODBC connectivity. Poor backwards compatibility and performance issues with subscribing applications, including MicroStrategy.

No, we didn't have enough data to really press it. The TF-6 at the time could support towards 64TB. We were using 10TB. When running queries natively, it processed most large data queries quickly.

Netezza promoted MapReduce functionality as add-on software, but I thought the support for it was very poor. I wasn't aware of any community that was able to get that up and running.

• Speed
• storage
• RAM

all of which contribute to large capacity.

Faster data processing compared to commodity servers.

In-DB processing with SAS Analytics, since this is supposed to be an analytics server so the expectation is there.

Three-plus years.

No.

No.

Eight out of 10.

Unix, commodity server. Switched to check this technology.

SAS server (Unix) and data storage only.

Expensive to maintain compared to other solutions.

Teradata and Greenplum.

Make sure to check the capability regarding in-DB processing with the application you will be using with this appliance. I am using SAS and it's a dis-appointment due to limited in-DB processing, including data connection pool, that was never resolved by both SAS and IBM Netezza.