Kognitio vs. OpenText Vertica

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Kognitio
Score 9.0 out of 10
N/A
WX2 is the data and analytics focused data warehouse appliance solution from UK company Kognitio.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
KognitioOpenText Vertica
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
KognitioOpenText 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
KognitioOpenText Vertica
Best Alternatives
KognitioOpenText Vertica
Small Businesses

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All AlternativesView all alternativesView all alternatives
User Ratings
KognitioOpenText Vertica
Likelihood to Recommend
9.0
(0 ratings)
8.0
(0 ratings)
Support Rating
-
(0 ratings)
7.9
(0 ratings)
User Testimonials
KognitioOpenText Vertica
Likelihood to Recommend
What I like most is the IN Memory capability it is doing, as we all know RAM is faster than disk. The capability to connect different databases. Beginners should also take note of the Data Disk Management because anytime it could go wrong, you should have experience in dealing with this kind of event.
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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
  • Ultra fast query results.
  • IN Memory Database.
  • Easy integration to reporting services.
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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
  • Problems Could Be Encountered is particularly pronounced in more complex analyses.
  • Categorical variables are often not precise enough
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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
The understandable and complete tables and graphs, the cleaning methods and the way of encrypting the data are quite feasible, which does not help to prepare our data, it helps that the data that is thrown as results is separated from each other, the process prior to structuring requires high-level advice and is somewhat time-consuming, there is a risk that they overwrite the data themselves by accident at a later time
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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
  • The implementation of the formats to integrate the users we have and the program is also good.
  • I also improve the control of aspects related to the work environment
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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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ScreenShots