Teradata: All content tagged as Teradata in NoSQL databases and polyglot persistence
Update: I’d like to thank the people that pointed out in the comment thread that I’ve messed up quite a few aspects in my comments about the report. I don’t believe in taking down posts that have been out for a while, so please be warned that basically this article can be ignored.
Thank you and my apologies for those comments that were a misinterpretation of the report..
This is the Q1 2014 Forrester Wave for Hadoop:
A couple of thoughts:
Cloudera, Hortonworks, MapR are positioned very (very) close.
- Hortonworks is position closer to the top right meaning they report more customers/larger install base
MapR is higher on the vertical axis meaning that MapR’s strategy is slightly better.
For me, MapR’s strategy can be briefly summarized as:
- address some of the limitations in the Hadoop ecosystem
- provide API-compatible products for major components of the Hadoop ecosystem
- use these Apache product (trade marked) names to advertise their products
I think the 1st point above explains the better positioning of MapR’s current offering.
Even if Cloudera has been the first pure-play Hadoop distribution it’s positioned behind behind both Hortonworks and MapR.
IBM has the largest market presence. That’s a big surprise as I’m very rarely hearing clear messages from IBM.
IBM and Pivotal Software are considered to have the strongest strategy. That’s another interesting point in Forrester’s report. Except the fact that IBM has a ton of data products and that Pivotal Software is offering more than Hadoop, I don’t know what exactly explains this position.
The Forrester report Strategy positioning is based on quantifying the following categories: Licensing and pricing, Ability to execute, Product road map, Customer support. IBM and Pivotal are ranked the first in all these categories (with maximum marks for the last 3). As a comparison Hortonworks has 3/5 for Ability to execute — this must be related only to budget; Cloudera has 3/5 for both Ability to execute and Customer support.
Pivotal is the 3rd last in terms of current offering. I guess my hypothesis for ranking Pivotal as 1st in terms of strategy is wrong.
Microsoft who through the collaboration with Hortonworks came up with HDInsight, which basically enabled Hadoop for Excel and its data warehouse offering, it positioned the 2nd last on all 3 axes.
No one seems to love Microsoft anymore.
While not a pure Hadoop player, DataStax has been offering the DataStax Enterprise platform that includes support for analytics through Hadoop and search through Solr for at least 2 years. That’s actually way before anyone else from the group of companies in the Forrester’s report had anything similar1.
This report focuses only on “general-purpose Hadoop solutions based on a differentiated, commercial Hadoop distribution”.
You can download the report after registering on Hortonwork’s site: here.
DataStax is my employer. But what I wrote is a pure fact. ↩
Original title and link: The Forrester Wave for Hadoop market ( ©myNoSQL)
Earlier today I’ve posted about Teradata’s take on the evolution of databases. As expected, everything is safe and under control. Now this report from Larry Dignan for ZDNet about Teradata Q4 earnings call presents Teradata’s perspective about Hadoop:
Teradata’s fourth quarter earnings were solid, but analysts peppered management with questions about Hadoop as data warehouse revenue worries persist.
Teradata CEO Mike Koehler and CFO Steve Scheppmann talked Hadoop throughout the company’s conference call. Was Hadoop taking Teradata’s business away? What’s the revenue hit? Can Teradata co-exist?
Once again everything is safe with a bright future. Until it isn’t anymore and Hadoop eats the enterprise data warehouse space. In Teradata’s defense, they’ve been one of the first companies that has looked seriously at Hadoop and came up with a coherent positioning.
Original title and link: Hadoop and Teradata’s business ( ©myNoSQL)
Simply put, Hadoop becomes the staging area for “raw data streams” while the EDW stores data from “operational systems”. Hadoop then analyzes the raw data and shares the results with the EDW. […] The paper then positions Hadoop as an active archive. I like this idea very much. Hadoop can store archived data that is only accessed once a month or once a quarter or less often.. and that data can be processed directly by Hadoop programs or shared with the EDW data using facilities such as Teradata’s SQL-H, or Greenplum’s External Hadoop tables (not by HAWQ, though… see here), or by other federation engines connected to HANA, SQL Server, Oracle, etc.
It’s an interesting positioning of Hadoop. And it’s very similar to the approach Linux has taken when penetrating the walls of enterprises. Then it slowly replaced pretty much everything.
In the early days—we are still in those days, the EDW vendors could still believe this story: Hadoop is complicated and meant for batch processing and it lacks the tools and refinements built over years in EDW.
But the story is starting to change. Fast. Hadoop is becoming more of a platform (YARN), it gets support for (almost) real-time querying (Impala, Project Stinger, HAWQ, just to name a few), and Hadoop leaders are signing partnerships with challengers and incumbents of the big data market at a rate that I don’t think I’ve seen before.
In the end, guess who will become the pillar of the big data platforms: the solution storing all the data or those tools being able to process, indeed very fast and with much control, limited amounts of that data?
✚ The Cloudera-Teradata paper titled “Hadoop and the Data Warehouse: When to Use Which” can be found here.
Original title and link: Hadoop and the EDW ( ©myNoSQL)
In the series of Big Data for C-Suites, here’s a video from Teradata:
Notice how this one focuses on two dimensions only: keywords and Teradata. For now Hortonworks’s Big Data and Hadoop for C-Suites resonates better with me.
Original title and link: Big Data for C-Suites: Teradata and Big Data the Best Decision Possible ( ©myNoSQL)