Big Data // Big Data Analytics
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1/30/2014
09:06 AM
Doug Henschen
Doug Henschen
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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.
9 of 17

InfiniDB counts on Apache Hadoop 
 
Analytical DBMS: InfiniDB (formerly Calpont). 
In-memory DBMS: None. 
Hadoop distribution: None.  
Stream-processing technology: None. 
Hardware/software systems: None (software-only vendor).
InfiniDB is the new name for the database management system formerly known by the company name, Calpont. This 14-year-old firm is on its fourth-generation massively parallel processing, columnar DBMS. The new product name is part of a push to step up sales and marketing efforts and get beyond the current base of about 50 customers. 
The InfiniDB makeover isn't just a name change. The company has reengineered the DBMS to run on top of the Hadoop Distributed File System for SQL-on-Hadoop analysis -- much as Pivotal did with Greenplum to create HAWQ. Conventional deployment options include Linux, Windows, or cloud on Amazon Web Services. The company also open sourced InfiniDB under the GNU General Public License, a choice it made because it's a MySQL storage engine. The commercially supported Enterprise edition adds utilities for administration and automation as well as a management console.
The InfiniDB technology is most comparable to that of HP Vertica and Actian Matrix (formerly Actian ParAccel), but company executives claim that automated partitioning features make it easier to manage than these rivals. The company also claims SQL-on-Hadoop query performance advantages over Cloudera Impala, Hive, and other approaches. These assertions won't win many friends and alliances among Hadoop distributors, but the company is counting on aggressive pricing to win over Hadoop users and would-be DBMS customers.

InfiniDB counts on Apache Hadoop

Analytical DBMS: InfiniDB (formerly Calpont).
In-memory DBMS: None.
Hadoop distribution: None.
Stream-processing technology: None.
Hardware/software systems: None (software-only vendor).

InfiniDB is the new name for the database management system formerly known by the company name, Calpont. This 14-year-old firm is on its fourth-generation massively parallel processing, columnar DBMS. The new product name is part of a push to step up sales and marketing efforts and get beyond the current base of about 50 customers.

The InfiniDB makeover isn't just a name change. The company has reengineered the DBMS to run on top of the Hadoop Distributed File System for SQL-on-Hadoop analysis -- much as Pivotal did with Greenplum to create HAWQ. Conventional deployment options include Linux, Windows, or cloud on Amazon Web Services. The company also open sourced InfiniDB under the GNU General Public License, a choice it made because it's a MySQL storage engine. The commercially supported Enterprise edition adds utilities for administration and automation as well as a management console.

The InfiniDB technology is most comparable to that of HP Vertica and Actian Matrix (formerly Actian ParAccel), but company executives claim that automated partitioning features make it easier to manage than these rivals. The company also claims SQL-on-Hadoop query performance advantages over Cloudera Impala, Hive, and other approaches. These assertions won't win many friends and alliances among Hadoop distributors, but the company is counting on aggressive pricing to win over Hadoop users and would-be DBMS customers.

9 of 17
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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.
D. Henschen
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D. Henschen,
User Rank: Author
2/4/2014 | 9:17:12 PM
Re: What about Personalized Big Data Analytics?
Once, again, as I've pointed out to others who didn't read the introduction, these are big data anaytics platforms -- the relational databases (for warehouses and marts) and Hadoop platforms that are the underpinning for the vast majority of analytic persuits. As pointed out in the introduction, this is not about pure analytics vendors such as SAS, Alpine Data Labs, Revolution Analytics, the whole R community or, for that matter, more BI-focused vendors such as Actuate, QlikTech, Tableau, MicroStrategy, etc. Nor is it about NoSQL and NewSQL databases, which are predominatly (though not exclusively) used to run high-scale transactional applications.
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