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.
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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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D. Henschen
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D. Henschen,
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1/30/2014 | 11:52:39 AM
It's time for this update
It has been little more than two years since we published our 12 Top Big Data Analytics Players collection, but so much has changed and so many new players have emerged that we needed this update. Over the last 26 months, all the big data-management vendors -- IBM, Microsoft, Oracle, SAP, Teradata -- have really embraced Hadoop. And whether they're adding SQL-on-Hadoop options -- a la Actian, InfiniDB/Calpont, and Pivotal -- or exploiting unprecidented levels of RAM -- as with Kognitio and SAP -- database management system suppliers are changing the scope and speed of their analysis capabilities.

The biggest change, though, is that practitioners are considering the data that they have on hand, the data that they're currenlty throwing away, and the data that they could collect with sensors or smart phones. They're considering all-new applications and, in some cases, entirely new business models. Innovaters may not want to delay or get their hands too dirty with all this technology, however, so we're seeing cloud options from 1010data, Amazon Web Services and others gathering steam.

We may have reached the end of the beginning of the big data era. But it's time to move beyond the speculative hype and get down to the business of on creating breakthrough applications that deliver value. Let 2014 be the year we shift from focusing on what could be to what is actually happening in the world of big data analysis.  
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.
mhummel515
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mhummel515,
User Rank: Apprentice
1/30/2014 | 12:09:03 PM
ParStream - real-time database for big data analytics
Hi Doug,

I very much appreciate your update on the big data analytics vendor market. 

I am curious to find out why you did not include ParStream in your list of big data analytics players. Agreed that the majority of our customers is still in Europe but through our strong presence in Cupertino and Boston we have won numerous customers in the US.

Our focus is on Fast Data - continuous data import at very high bandwidth combined with sub-second response times on billions of data records. 

Through partnerships with leading front-end and ETL tool providers AND Hadoop we offer a super-fast analytics solution that outperforms all product on your list.

I am happy to share with you performance benchmarks and introduce you to our reference customers.

Best
Mike
CEO ParStream
D. Henschen
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D. Henschen,
User Rank: Author
1/30/2014 | 12:53:55 PM
Re: ParStream - real-time database for big data analytics
Thanks for your note. I don't hear much about ParStream, and your list of customers isn't studded with well-know companies. I excluded Exasol for much the same reason -- a number of customers in Germany, but not a presence in North America where we get the vast majority of our readership. Your technology is of interest, however, so feel free to contact me, particularly with customer case example.
mhummel515
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mhummel515,
User Rank: Apprentice
1/30/2014 | 1:09:00 PM
Re: ParStream - real-time database for big data analytics
Hi Doug,

I appreciate your interest in ParStream and will make sure to get in contact to provide insights into our product and customer base.

Unfortunately, some of our customers are "shy" and do not want to be named publicly. This unfortunately includes the US customers.

Looking forward to get in touch.



Mike
Laurianne
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Laurianne,
User Rank: Author
1/30/2014 | 1:03:16 PM
Important Big Data Context
Doug has supplied important context for those people choosing between big data analysis vendors. Please tell us if there are aspects you would like more/less detail on when we do the next roundup. Readers, are you surprised by how much support Hadoop has won from the bigs in the last 24 months?
anon4507650351
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anon4507650351,
User Rank: Apprentice
2/3/2014 | 9:03:38 AM
Re: Important Big Data Context
Hi Laurianne, as mentioned in another post, Doug's article provides a useful analysis of the Big Data marketplace from a platforms perspective. Since we are still in the infancy of BD (vs BI), the market is changing rapidly and there will be significant consolidation in the next year or two (acquisitions of small players by the giants). I predict that the largest beneficial use of BD will be for machine learning through the Internet of Things (sensors, etc). There are currently only a small number of players focusing on this aspect of BD. It will be interesting to track the development of Hadoop specifically whether companies go pure open source ala Hortonworks or veer more towards proprietery. I suspect the latter.

Raj
cbabcock
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cbabcock,
User Rank: Strategist
1/30/2014 | 2:41:29 PM
Revolutionary times, now and then
Doug, you're right, this is a revolutionary time in data management. The last time was when relational database first appeared. I remember sitting through meeting after meeting with then-major vendors, Software AG of North America in Reston, Va.,(Adabas) and John Cullinane, CEO at Cullinane Software (IDMS). They were furious that their partner, IBM, was coming into "their" data management market. "There's no need for IBM to do that." Well, IBM had invented ad hoc data handling and SQL queries. "Their" systems didn't do that. It was a quick lesson in how vendors get flanked. NoSQL systems don't have the same elegance of relational's deisgn, but they're too useful with unstructured data to get swept back under the rug.
HM
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HM,
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1/30/2014 | 3:03:02 PM
Big Data Solution
Doug, one other open source technology to mention at the top of the decision tree one should consider is HPCC Systems from LexisNexis, a data-intensive supercomputing platform for processing and solving big data analytical problems. Their open source Machine Learning Library and Matrix processing algorithms assist data scientists and developers with business intelligence and predictive analytics. Its integration with Hadoop, R and Pentaho extends further capabilities providing a complete solution for data ingestion, processing and delivery. In fact, both libhdfs and webhdfs implementations are available. More at http://hpccsystems.com/h2h 

 
 
EB Quinn
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EB Quinn,
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1/31/2014 | 8:00:42 AM
Only 16?
There are many more of these "top" solutions, and some of these on the "top" list make no sense whatsoever.  What is the criteria?  Does it have to include Hadoop?  MPP?  Advertiser?  Market share?  Some of the vendors you have included have very little market share, like Pivotal and Microsoft (unless you are incuding Excel).  Where is SAS?  Palantir?  Qlik?  Platfora?  They may not have Hadoop distributions, but they can work with Hadoop just fine (and Platfora is natively based on Hadoop).  Agree with the comment that HPCC should be on this list, way higher than a bunch of the others in terms of proven high end analytics with actual customers.  What is a "platform?"  Cringing.

 

 

 
D. Henschen
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D. Henschen,
User Rank: Author
1/31/2014 | 2:03:48 PM
Read the introduction
This is about platforms for big-data analysis -- as in DBMSs and Hadoop - and I state very clearly in the intro that it does not address analytics companies -- SAS, Qlik, and others you mention -- that focus almost entirely on analytics alone and that tend to work with these platforms. Nor does this address NoSQL or NewSQL databases, which we'll address in a separate collection.
srini s
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srini s,
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1/31/2014 | 2:36:25 PM
A collection of marketing flyers from 16 vendors
This is a shallow post to introduce a newbie to a biased view of what is available in the market (on Hadoop and it's related technology) if you want to venture into big data. Instead of sitting through a marketing presentation of each of these vendors, or going through their websites, you can see it here. I would have personally preferred the links to the home page of these technologies. It doesn't seem to take an unbiased approach on merits and pitfalls. Why would you choose one over the other.  A comparison on the technologies based on its focus (which of the VVV that it attacks), what is the TCO, quantifying the BIG and qualifying the ANALYTICS in big data analytics. Both Cloudera and Hortonworks are there. We have HP and IBM too and AWS... meh! Could have included some SAN storage providers too :) There seems to be no plane for comparison. There is no connecting element between pages. I would have liked a better organization of thoughts. 

This would have been a ground breaking post in 2006. But now.. pass!

-Srini

 
D. Henschen
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D. Henschen,
User Rank: Author
1/31/2014 | 3:00:19 PM
Re: A collection of marketing flyers from 16 vendors
Srini, Thanks for your comments. Actian, Cloudera, Hortonworks, MapR, and Pivotal didn't exist in 2006, and most have arrived since 2010. Among the giants, IBM, Microsoft, Oracle, SAP and Teradata have only added support for Hadoop in the last two to three years. "Connecting elements" across all 16 include insight on their offerings for analytical DBMS, in-memory options, streaming options, Hadoop distributions, and hardware/software appliances. And if you read each analysis, I think that you'll find that it's far from a regurgitation of marketing brochures. There are plenty of insights into strategy, market approach, strengths and weaknesses and more.  
srini s
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srini s,
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1/31/2014 | 6:10:40 PM
Re: A collection of marketing flyers from 16 vendors
Doug - What I meant by 2006 was not the freshness of the information presented, but the fact that big data is a household term (of sorts) and an authoritative article in this space at 2014 needs more depth and breadth.   

With respect to the comparison on Analytic DBMS, In-memory etc, it was a good metric but a bad choice for this post. In fact, it would have been good if it was a single matrix comparing the 16 technologies (and a few more) against these options (and a few more). Still, I am not able to find out who your intended audience was. It seems to be catering to management, tech, architects and infrastructure admins partially but none fully :(

Neverthess, I apologize for coming out strong on you. Take it as constructive criticism, if you can :)

Cheers

Srini

 
anon4507650351
IW Pick
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anon4507650351,
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2/3/2014 | 8:52:05 AM
Re: A collection of marketing flyers from 16 vendors
Srini/Doug, I have been involved in coming up with my company's Big Data strategy including a BDaaS offering and go-to-market stategy. My research including deep dive sessions (architecturally, technically and commercially) with many of the players listed here indicate the same findings as Doug's article. Each vendor approaches the problem from their own perspective based on their previous expertise (e.g. hardware specialisation like HP, storage perspective like EMC/Pivotal, pureplay DB/analytics, etc). Some like IBM and Oracle have thrown billions of $$ at the problem, but mostly use BD as pull through for HW/SW sales. There are relatively a small number of pure BD companies like Palantir.  Most are glorified BI specialists jumping on the BD bandwagon who cannot go one level below their vaporware. There seems to be a gap in the market for a end-to-end offering which is technology independent. Very difficult to achieve and implement this since it it the large players who keep up better with the changing landscape. So overall, a good high level analysis Doug which allows interested parties to narrow down the playing field before commencing more deep dive analysis.

Raj
D. Henschen
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D. Henschen,
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2/3/2014 | 12:47:07 PM
Re: A collection of marketing flyers from 16 vendors
Excellent take, Raj. The likes of IBM, Oracle and Teradata have certainly checked the Hadoop box, but I wonder how hard they push it or whether they try to keep it in a high-scale storage role while favoring their incumbent technologies for the analysis. Cloudera and MapR are saying you can do more and challenge incumbent technologies while Hortoworks holds short of such bold claims -- clearly not wanting to challenge partners Microsoft, Teradata and SAP. The independent DBMS vendors have various strategies and capabilities around working with Hadoop, and they generally don't challenge EDW vendors -- only the high-scale data mart/analytics opportunity. All of these vendors offer "Big Data Analytics Platforms," but they're coming at it from secular angles.
bigdatarelated
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bigdatarelated,
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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.
CFree22
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CFree22,
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2/4/2014 | 7:24:14 PM
What about Personalized Big Data Analytics?
Like the other comments inquired, how were these determinations made regarding the top 16 Big Data Analytics Platforms? What data was used? (Was it based on scalability factors or the number of companies in an industry that used it?) Why wasn't Actuate included? I find this fascinating especially since the BIRT Analytics software, and BIRT reporting software is used for big data analytics. Hortonworks, Actian, and Amazon web services have partnered with Actuate for big data deployments and they use BIRT technology. Do you have feedback from the business users and the end users comparing their experiences with the platforms? I am just curious what that kind of data looks like. How does the security of the data and the scalability come into play when evaluating these platforms? What about the time it takes to implement the platforms and get everyone trained in using them--was that a factor? What makes some better than others aside from the purpose of their use? I really appreciate articles that provide this kind of side by side comparison, and I would like to see more of it in the future. I wonder how small to medium busineses handle this big kind of technology though. Big enterprises definitely need these big platforms. Thank you for your article. I look forward to reading more. :)
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.
CFree22
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CFree22,
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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,
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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).

 
weckerson
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weckerson,
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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
2/11/2014 | 1:28:26 PM
Re: Bravo
Thanks, Wayne. Coming from such an esteemed expert, I'm flattered.
Akon786
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Akon786,
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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?
KenB037
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KenB037,
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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!
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