
This article was originally published by forbes.com and can be viewed in full here
The Big Data industry has matured to the point where there are now established markets for the various categories of products and services, which make up the industry. My clients often ask me about the best big data vendors they might use and my answer is that this very much depends on the type of service they are after.
Each service category has its own movers, shakers and heel-snapping underdogs. So I thought it would be worth giving a brief overview of the different types of big data service categories and the businesses jostling for their share of the $125 billion (and rising) big data and analytics market.
It’s worth pointing out that there is a large amount of vertical integration in the industry, with big names such as IBM -2.29% , SAP, Oracle-1.49%, Dell , Hewlett-Packard-1.92% and Amazon offering services which fall into several of these categories. In other words the lines between these categories are not always clearly drawn. Nevertheless there are certain names, which are more strongly associated with particular links in the chain that make up the big data analytics industry.
Data vendors
These are the guys who sell you the raw material of pure, unadulterated data so that you can perform your big data analytics. Commercial big data projects often rely on a mixture of internal and external, third party data. For external, bought-in data, frequently used sources include credit agencies such as Experian who provide demographic data and LexisNexis which sells data related to legal and business proceedings. Other services such as BDEX and DatastreamX and Microsoft Azure Datamarket act as data marketplaces, where businesses can offer their own data for sale as well as buy it in.
Infrastructure and Platform Providers
These are mostly vendors which offer their own installations and services based around the most popular open source Big data technologies such as Hadoop and Spark as well as noSQL database formats such as MongoDB or Cassandra. Market-leading names in this field include Cloudera, Hortonworks, MapR, IBM and Amazon. These companies generally offer customized installations of Hadoop alongside particular analytics or storage solutions tweaked to their clients’ needs.


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)