16 Top Big Data Analytics Platforms - InformationWeek

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Data Management // 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.
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1010data puts analytics in the cloud 
 
Analytical DBMS: 1010data columnar analytical database. 
In-memory DBMS: None. 
Stream-analysis option: None. 
Hadoop distribution: None.  
Hardware/software systems: Not applicable.
New York-based 1010data launched its analytical, private-cloud service way back in 2000, building a base of customers on Wall Street. Marquis customers include NYSE Euronext and a number of big banks, but the company has also branched out into retail, CPG, gaming, healthcare, government, and telecommunications.
1010data's columnar database supports massively parallel processing for scalability, but it's a proprietary design with its own query language that supports a subset of SQL functions plus broader query types including graph and time-series analyses. It also handles semi-structured data such as social network and machine data. Beyond the database, the company offers a complete stack including data integration, reporting, and data-visualization tools, as well as advanced analytic functions including statistical analysis, optimization, and machine learning.
1010data's private-cloud approach relieves customers of the burden of managing and scaling infrastructure. Centralized management and access controls and APIs support integration with back-end systems as well as broad access to information with 'HIPAA-grade' security. The company has more than 250 customers. In contrast to a cloud provider such as Amazon, which delivers standardized (very-low-cost) services to tens of thousands of customers, 1010data is a custom services provider that crafts private-cloud applications and capabilities matched to customer needs.

1010data puts analytics in the cloud

Analytical DBMS: 1010data columnar analytical database.
In-memory DBMS: None.
Stream-analysis option: None.
Hadoop distribution: None.
Hardware/software systems: Not applicable.

New York-based 1010data launched its analytical, private-cloud service way back in 2000, building a base of customers on Wall Street. Marquis customers include NYSE Euronext and a number of big banks, but the company has also branched out into retail, CPG, gaming, healthcare, government, and telecommunications.

1010data's columnar database supports massively parallel processing for scalability, but it's a proprietary design with its own query language that supports a subset of SQL functions plus broader query types including graph and time-series analyses. It also handles semi-structured data such as social network and machine data. Beyond the database, the company offers a complete stack including data integration, reporting, and data-visualization tools, as well as advanced analytic functions including statistical analysis, optimization, and machine learning.

1010data's private-cloud approach relieves customers of the burden of managing and scaling infrastructure. Centralized management and access controls and APIs support integration with back-end systems as well as broad access to information with "HIPAA-grade" security. The company has more than 250 customers. In contrast to a cloud provider such as Amazon, which delivers standardized (very-low-cost) services to tens of thousands of customers, 1010data is a custom services provider that crafts private-cloud applications and capabilities matched to customer needs.

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shane88
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shane88,
User Rank: Apprentice
10/9/2017 | 5:35:16 AM
Re: It's time for this update
This tool might also help: JSON formatter. Have a nice day!
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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0%
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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100%
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
50%
50%
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
50%
50%
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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50%
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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0%
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).

 
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