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Classifying Today’s “Big Data Innovators”
These 13 vendors distribute 16 unique data management products

By

Editor’s note: The piece below by   first appeared on the Hadapt blog and is republished with permission here. The framework presented provides insight into the very dynamic market around “Big Data Innovators” and should be of use for classifying many other firms in this interesting space. -bg

Recently InformationWeek published a piece, authored by Doug Henschen, that listed 13 innovative Big Data vendors. The complete list is reproduced below:

1.  MongoDB
2.  Amazon (Redshift, EMR, DynamoDB)
3.  Cloudera (CDH, Impala)
4.  Couchbase
5.  Datameer
6.  Datastax
7.  Hadapt
8.  Hortonworks
9.  Karmasphere
10.  MapR
11.  Neo Technology
12.  Platfora
13.  Splunk

Big-Data3These 13 vendors distribute 16 unique data management products (since both Amazon and Cloudera offer multiple distinct data management/processing systems), all of which push the boundary on Big Data management.

In this post I will attempt to subcategorize these 16 products into a competitive grouping, where products placed inside the same group can be considered replacements for each other (and hence are competitive), and each group is complementary to every other group.

Before starting this classification, I will remove three products that, while potentially being interesting from a Big Data perspective, are often used outside of what has become known as the “Big Data realm”, and therefore their primary competitors did not make it on the InformationWeek list. These three products are Splunk (which typically competes with companies focused on the security, compliance, and IT operations management verticals), Amazon Redshift (which typically completes with traditional MPP database vendors), and Neo Technology (which, although usually classified as a “NoSQL database”, its focus on graph data makes it highly unique from a technology and use case perspective relative to the other NoSQL databases on this list).

The remaining 13 products can be classified into four distinct groups:
1.  Operational data stores that allow flexible schemas
2.  Hadoop distributions
3.  Real-time Hadoop-based analytical platforms
4.  Hadoop-based BI solutions

Group 1 (operational data stores that allow flexible schemas)
This group is composed of database products that can be used to manage active data for dynamic applications with hard to define (or hard to predict) schemas. The database must be optimized for inserting, retrieving, updating, or deleting individual data items in real-time (latencies on the order of milliseconds), but should also support some sort of interface for performing analysis of the data stored within. The dynamic nature of the typical use case for databases in this group implies a NoSQL interface, and either a key-value or document-store retrieval model. From the InformationWeek list, MongoDB, DynamoDB, Couchbase, and Datastax all fit in this category. Although there are some significant technical differences between these products, they can nonetheless be roughly described as potential replacements for each other in Group 1 use cases.

Group 2 (Hadoop distributions)
The products in this group are designed for very different situations than Group 1. Hadoop is typically used for large scale data analysis and batch processing. Rather than inserting, retrieving, updating, or deleting individual data items, Hadoop is optimized for scanning through large swaths of data, processing and analyzing the data as it proceeds. Hadoop has become the poster-child for “Big Data” due to its proven massive scalability, and its ability to handle the “variety” aspect of Big Data (since Hadoop does not require data to fit neatly into rows and columns in order to be analyzed and processed). From the InformationWeek list, Cloudera, Hortonworks, MapR, and Amazon EMR all fit in this category.

Group 3 (real-time Hadoop-based analytical platforms)
Group 3 takes Hadoop to the next level, transforming it from a mere batch processing system to a full-fledged analytical platform that can answer queries in real-time. Furthermore, by adding a more robust SQL interface to Hadoop (in addition to industry-standard ODBC connectors), group 3 products help to hide the complexity of Hadoop and the need for Hadoop specialists, since traditional business intelligence and visualization tools are now able to interface directly with data stored inside Hadoop. From the InformationWeek list, Hadapt clearly fits in this category, and with certain caveats, so does Cloudera Impala (the caveats are that as of the time of writing this blog post (a) Impala is an extremely young codebase and is still only in beta (b) Impala only supports a small subset of SQL and does not support UDFs or other ways to combine structured and unstructured data in the same query, so calling it an “analytical platform” might be a bit of a stretch).

Group 4 (Hadoop-based BI solutions)
Often lumped together with group 3 products,  group 4 products are often confused as being competitive with group 3 products. However, just as business intelligence tools and analytical database solutions are highly complementary and were often packaged together in the pre-Hadoop world, the same is true in the Hadoop/Big Data world. Therefore, Datameer, Karmasphere, and Platfora, all of which function as a business intelligence layer above Hadoop, are capable of working closely with the group 3 products (with announcements along these lines already starting to begin).

In conclusion, although “Big Data” is an enormous and rapidly growing market, one single data management software product is not going to rule the market. Rather, there are four major groups of data management solutions within the Big Data space; and while there is fierce competition within each group, at the macro level these groups can not only co-exist, but are highly complementary. In the long run, it is likely that the 2-3 leaders in each group will emerge and share the Big Data pie.

Read the original blog entry...

About Bob Gourley
Bob Gourley writes on enterprise IT. He is a founder and partner at Cognitio Corp and publsher of CTOvision.com

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Cloud Expo 2013 East Opening Keynote by IBM
In this Cloud Expo Keynote, Danny Sabbah, CTO & General Manager, Next Generation Platform, will detail the critical architectural considerations and success factors organizations must internalize to successfully implement, optimize and innovate using next generation architectures.
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There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Get a jump on that rapidly evolving trend at Big Data Expo, which we are introducing in June at
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@CloudExpo Blogs
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If we look at slow, traditional IT and jump to the conclusion that just because we found its issues intractable before, that necessarily means we will again, then it’s time for a rethink. As a matter of fact, the world of IT has changed over the last ten years or so. We’ve been experiencing unprecedented innovation across the board – innovation in technology as well as in how people organize and accomplish tasks. Let’s take a look at three differences between today’s modern, digital context for enterprise IT as compared to conventional wisdom – wisdom that may have applied only a handful ...
The (re?)emergence of Microservices was especially prominent in this week’s news. What are they good for? do they make sense for your application? should you take the plunge? and what do Microservices mean for your DevOps and Continuous Delivery efforts? Continue reading for more on Microservices, containers, DevOps culture, and more top news from the past week. As always, stay tuned to all the news coming from@ElectricCloud on DevOps and Continuous Delivery throughout the week and retweet/favorite to get your favorite pieces featured in our weekly recap.
Over the past year, Microsoft has been introducing Azure Resource Manager (ARM) as the preferred way to provision and manage resources in its Azure cloud. ARM is the successor to the original Service Management model, also known as “Classic.”[1] While Classic will continue to be supported for the foreseeable future, ARM is the preferred deployment model and all new Azure features are being released on ARM only. Here is an overview ARM and the new features it provides.
In the middle of World War II, very basic and primitive computers were designed to improve accuracy for naval gunfire. The first computers ran complex mathematical applications to calculate trajectories and gunfire from large battleships. The size of the computer was huge and was made up of vacuum-tube technology. You could literally walk into the computer. (And needed to, when a tube went bad and you had to replace it.)
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My colleague, Jennelle Crothers, and I got a chance to chat about the usability and ease of use in this episode of Windows 10 series in TechNet Radio. She’s great and we had much fun doing it. Jennelle did a quick demo on how to make Windows 10 even easier to use.
With the proliferation of both SQL and NoSQL databases, organizations can now target specific fit-for-purpose database tools for their different application needs regarding scalability, ease of use, ACID support, etc. Platform as a Service offerings make this even easier now, enabling developers to roll out their own database infrastructure in minutes with minimal management overhead. However, this same amount of flexibility also comes with the challenges of picking the right tool, on the right provider and with the proper expectations. In his session at 18th Cloud Expo, Warner Chaves, Princ...
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cloudcomputingexpo
2010west.sys-con.com

 
    Virtualization Expo West
virtualization
2010west.sys-con.com
    Cloud Expo Europe
cloudexpoeurope2010.
sys-con.com

 
    Cloud Expo East
cloudcomputingexpo
2010east.sys-con.com

 
    Virtualization Expo East
virtualizationconference
2010east.sys-con.com
    Cloud Expo West
cloudcomputingexpo
2009west.sys-con.com

 
    Virtualization Expo West
virtualizationconference
2009west.sys-con.com
    GovIT Expo
govitexpo.com
 
    Cloud Expo Europe
cloudexpoeurope2009.sys-con.com
 

Cloud Expo 2011 Allstar Conference Faculty

S.F.S.
Dell

Singer
NRO

Pereyra
Oracle

Ryan
OpSource

Butte
PwC

Leone
Oracle

Riley
AWS

Varia
AWS

Lye
Oracle

O'Connor
AppZero

Crandell
RightScale

Nucci
Dell Boomi

Hillier
CiRBA

Morrison
Layer 7 Tech

Robbins
NYT

Schwarz
Oracle

What The Enterprise IT World Says About Cloud Expo
 
"We had extremely positive feedback from both customers and prospects that attended the show and saw live demos of NaviSite's enterprise cloud based services."
  –William Toll
Sr. Director, Marketing & Strategic Alliances
Navisite
 


 
"More and better leads than ever expected! I have 4-6 follow ups personally."
  –Richard Wellner
Chief Scientist
Univa UD
 


 
"Good crowd, good questions. The event looked very successful."
  –Simon Crosby
CTO
Citrix Systems
 


 
"It's the largest cloud computing conference I've ever seen."
  –David Linthicum
CTO
Brick Group