16 Top Big Data Analytics Platforms - InformationWeek
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16 Top Big Data Analytics Platforms

Data analysis is a do-or-die requirement for today's businesses. We analyze notable vendor choices, from Hadoop upstarts to traditional database players.
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HP HAVEn architecture taps Vertica 
 
Analytical DBMS: HP Vertica Analytics Platform Version 7 (Crane release). 
In-memory DBMS: Vertica is not an in-memory database, but with high RAM-to-disk ratios the company says it can ensure near-real-time query performance. 
Hadoop distribution: None.  
Stream-processing technology: None. 
Hardware/software systems: HP ConvergedSystem 300 for Vertica, plus a choice of reference architectures for Cloudera, Hortonworks, and MapR Hadoop distributions.
HP calls its big-data-platform architecture HAVEn, an acronym for Hadoop, Autonomy, Vertica, Enterprise Security, and 'n' applications. HP doesn't have its own Hadoop distribution, but it provides reference hardware configurations for leading Hadoop software distributors. Autonomy's IDOL software addresses search and exploration of unstructured. Vertica is HP's massively parallel processing columnar analytical DBMS designed for speedy analysis of massive, structured data sets. Competing with the likes of IBM PureData for Analytics (Netezza) and Pivotal Greenplum, Vertica is intended to complement rather than replace legacy enterprise data warehouse environments such as Teradata. 
With the Vertica 7 release, HP added a 'FlexZone' designed to let users explore data in large data sets before defining the database scheme and related analyses and reports. Release 7 is also integrated with Hadoop through Hive's HCatalog metadata store, giving users a way to explore data on HDFS in a tabular view.
HP's ArcSight Logger software for collecting and analyzing machine data and its Operational Analytics offerings give it more of an IT-centric spin on big-data analysis than most of its rivals. IBM, SAP, and Oracle, for example, are much deeper on data-integration, BI, and analytics software for business applications. If HP is your IT systems management and hardware vendor of choice, the HAVEn platform and its components complement Hadoop and investments in third-party data-management and analytics software.

HP HAVEn architecture taps Vertica

Analytical DBMS: HP Vertica Analytics Platform Version 7 (Crane release).
In-memory DBMS: Vertica is not an in-memory database, but with high RAM-to-disk ratios the company says it can ensure near-real-time query performance.
Hadoop distribution: None.
Stream-processing technology: None.
Hardware/software systems: HP ConvergedSystem 300 for Vertica, plus a choice of reference architectures for Cloudera, Hortonworks, and MapR Hadoop distributions.

HP calls its big-data-platform architecture HAVEn, an acronym for Hadoop, Autonomy, Vertica, Enterprise Security, and "n" applications. HP doesn't have its own Hadoop distribution, but it provides reference hardware configurations for leading Hadoop software distributors. Autonomy's IDOL software addresses search and exploration of unstructured. Vertica is HP's massively parallel processing columnar analytical DBMS designed for speedy analysis of massive, structured data sets. Competing with the likes of IBM PureData for Analytics (Netezza) and Pivotal Greenplum, Vertica is intended to complement rather than replace legacy enterprise data warehouse environments such as Teradata.

With the Vertica 7 release, HP added a "FlexZone" designed to let users explore data in large data sets before defining the database scheme and related analyses and reports. Release 7 is also integrated with Hadoop through Hive's HCatalog metadata store, giving users a way to explore data on HDFS in a tabular view.

HP's ArcSight Logger software for collecting and analyzing machine data and its Operational Analytics offerings give it more of an IT-centric spin on big-data analysis than most of its rivals. IBM, SAP, and Oracle, for example, are much deeper on data-integration, BI, and analytics software for business applications. If HP is your IT systems management and hardware vendor of choice, the HAVEn platform and its components complement Hadoop and investments in third-party data-management and analytics software.

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UrvashiS073
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UrvashiS073,
User Rank: Apprentice
4/27/2017 | 1:30:45 PM
IRI Voracity

I would add to this list IRI Voracity, the big data discovery, integration, migration, governance, and analytics platform introduced in 2016 to address the performance, security, quality, complexity and cost issues in legacy vendor and speciality tools.

eyu906
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eyu906,
User Rank: Strategist
1/6/2015 | 12:36:09 PM
Drill-downs?
Dell Boomi is the #1 cloud integration platform.  Are you going to drill down to help users regarding technology strategy?
KenB037
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KenB037,
User Rank: Apprentice
9/24/2014 | 10:27:52 PM
Great article! When is the next update?
Super overview article! I realize that it will be a lot of work, but it would be great if you decide to write an update sometime time soon.  I am already looking forward to it!
LesterK048
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LesterK048,
User Rank: Apprentice
8/8/2014 | 2:51:40 AM
Re: It's time for this update
A smaller company which can process big JSON data for easier visualization is json-csv.com. You may want to check it out.
bigdatarelated
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bigdatarelated,
User Rank: Apprentice
4/23/2014 | 11:24:38 AM
Re: A collection of marketing flyers from 16 vendors
Great article. I've added a link to it from  Bigdatarelated, a free big data community resource website.
Akon786
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Akon786,
User Rank: Apprentice
2/20/2014 | 6:39:55 AM
Bedrock Data Management Platform 2.0
Comprehensive and well rounded article.

Where does Bedrock Data Management Platform 2.0 figure in the game?
D. Henschen
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D. Henschen,
User Rank: Author
2/11/2014 | 1:28:26 PM
Re: Bravo
Thanks, Wayne. Coming from such an esteemed expert, I'm flattered.
weckerson
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weckerson,
User Rank: Apprentice
2/6/2014 | 4:33:06 PM
Bravo
Doug, 

Well done. This is a ton of work and well done! A great resource. 

 

Wayne
D. Henschen
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D. Henschen,
User Rank: Author
2/5/2014 | 9:18:53 AM
Re: What about Personalized Big Data Analytics?
Analytics tools and BI systems run on servers, but these systems are generally not scaled to handle big data. More often than not, these systems draw data from data warehouses or data marts. Increasingly, a larger-scale "platform" such as a massively parallel processing (MPP) database management system or Hadoop cluster is required to handle the volume and variety of data. Some analytics vendors, notably SAS but including others, are developing their own in-memory cluster software or implementations on top of Hadoop, but the vast majority of clients use analytics and BI software in combination with data-management platforms from third-party vendors like those covered in the collection above.

Confusing matters, many vendors above offer analytic capabilites -- IBM has SPSS and Cognos; SAP has BusinessObjects and Predictive Analysis; Oracle, Pivotal, and Teradata tap advanced SQL analytics, R and various partnerships with analytics vendors including SAS, etc. -- but they're not included in this collection because of those capabilites.

There are many options for smaller companies -- including cloud, price-competitive upstart vendors, and open source options. But where this is great data volume, variety, and velocity, there's a need for a high-scale platform or platforms to serve as the place where the analysis gets done (as with in-database or in-Hadoop analytics) or as the place from which subsets of data are drawn or analyzed (as in the case of Hadoop or data warehouse integration).

 
CFree22
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CFree22,
User Rank: Apprentice
2/5/2014 | 12:43:38 AM
Re: What about Personalized Big Data Analytics?
I apologize for being confused about this. The title just made it seem like big analytis platforms were going to be highlighted for their top features. So, Jaspersoft and the like are not considered to have big analytics platforms?  Do you think the platforms you metioned are worth the investment for smaller businesses or is that kind of analytics too cost-prohibitive? I think a lot of people are still confused about how big data can be made useful and applied to business analytics in general. 

Thank you for the side by side breakdowns of each platform.
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