IBM Netezza Performance Server vs. OpenText Vertica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Netezza Performance Server
Score 7.4 out of 10
N/A
Netezza Performance Server (NPS) is an add-on data warehouse solution available on Cloud Pak for Data System platform, built over open source and optimized for High Performance Analytics with built-in hardware acceleration. Netezza Performance Server was previously named IBM Performance Server for PostgreSQL (IPS).N/A
OpenText Vertica
Score 9.4 out of 10
N/A
The Vertica Analytics Platform supplies enterprise data warehouses with big data analytics capabilities and modernization. Vertica is owned and supported by OpenText.N/A
Pricing
IBM Netezza Performance ServerOpenText Vertica
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
IBM Netezza Performance ServerOpenText Vertica
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM Netezza Performance ServerOpenText Vertica
Best Alternatives
IBM Netezza Performance ServerOpenText Vertica
Small Businesses
Google BigQuery
Google BigQuery
Score 8.5 out of 10
Google BigQuery
Google BigQuery
Score 8.5 out of 10
Medium-sized Companies
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Cloudera Enterprise Data Hub
Cloudera Enterprise Data Hub
Score 9.0 out of 10
Enterprises
Oracle Exadata
Oracle Exadata
Score 10.0 out of 10
Oracle Exadata
Oracle Exadata
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM Netezza Performance ServerOpenText Vertica
Likelihood to Recommend
9.3
(0 ratings)
8.0
(0 ratings)
Support Rating
-
(0 ratings)
7.9
(0 ratings)
User Testimonials
IBM Netezza Performance ServerOpenText Vertica
Likelihood to Recommend
Netezza Performance Server enhances the data scientist's ability to rapidly design, train, and deploy machine learning models in the database. Netezza Performance Server is essential for implementing cognitive machine learning, providing data scientists with in-database analytics, and enabling them to collaborate on a single platform. Netezza Performance Server supports the use of built-in Spark as well as Python and R for rapid and sophisticated data science and machine learning adoption at scale.
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As someone just starting out with data analytics and warehousing vertica is a great tool for a small scale business. It has amazing performance and can scale upto TBs of data. It works well for any organization which has about 100 - 500 DAUs of the system. The system doesn't require a lot of ops overhead. Scaling for PB data and 1000s of DAU is vertica's weak point. The system is just not designed for large scale usage and still has a long way to go to improve scalability. There are experiments to run Vertica query engine on top of HDFS which seem promising, however - if you have the the Hadoop ecosystem you are better off going the HDFS + Presto/Impala/SparkSQL route. But if you are in the Hadoop ecosystem, you probably are already investing a lot in ops.
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Pros
  • The speed of operations is really second to none
  • The data control aspect is really effective and very useful
  • Stability and no latency issues notices during operations
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  • Column-oriented storage organization, which increases performance of queries.
  • Compression, which reduces storage costs and I/O bandwidth. High compression is possible because columns of homogeneous datatypes are stored together and because updates to the main store are batched.
  • Shared nothing architecture, which reduces system contention for shared resources and allows gradual degradation of performance in the face of hardware failure.
  • Easy to use and maintain through automated data replication, server recovery, query optimization, and storage optimization.
  • Support for standard programming interfaces ODBC, JDBC, ADO.NET, and OLEDB.
  • Integration to Hadoop with the capability to perform analytics on ORC and Parquet files directly.
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Cons
  • The cost is expensive for medium-sized and smaller companies.
  • IBM could bring back the technical account managers.
  • The procurement process is a hassle.
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  • One time, one of the nodes wasn't coming up because of some ambiguity with the local data. Vertica wasn't able to fix it by itself and we were trying to remove the node out of the database and we couldn't do it. It would be great if that could be addressed. Luckily when we rebooted the whole server, some of the dead transaction got flushed because of which vertica was able to recover and the node came up.
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Support Rating
No answers on this topic
HP/Micro Focus Vertica support is in par with other bigger vendors. In addition to this, there is enough best practices documentation available for some of the most common ways you will use Vertica that makes it easy to get Vertica up and running.
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Alternatives Considered
With a simple user interface and
access to IBM's online instructions, Netezza Performance Server is easy to
operate. It also has built-in contribution facilities, as well as good customer
support, to make the DBA's job easier.
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MySQL and MS SQL Server are both fantastic RDBMS products. MS SQL Server goes a bit further since it has the builtin analytical functions. But it only scales so far. Once the data goes beyond capacity, getting results out just does not happen anymore. IBM Netezza and Teradata were both appliances that required different expertise than we had in house. Vertica was able to do the same, and in some cases better, on commodity hardware (frankly in our case old servers that were slated for recycling!) and at a small scale. In other words, Vertica we could grow slowly over time. Infobright is a great log processing database but for the functions we were looking to serve it just didn't have some of the features Vertica had that we felt were show stoppers.
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Return on Investment
  • It allows us to work together simultaneously in the database to query our custom results.
  • It requires users to know the object name as it does not pop up in their text editor. Thus, users take more time in writing queries.
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  • Vertica increased our productivity in analyzing the data and validating simple proof of concepts with our data.
  • Results of analytical queries produced from Vertica are used by all departments as well as part of some of our products.
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