October 17, 2012

Hadoop/RDBMS integration: Aster SQL-H and Hadapt

Two of the more interesting approaches for integrating Hadoop and MapReduce with relational DBMS come from my clients at Teradata Aster (via SQL/MR and SQL-H) and Hadapt. In both cases, the story starts:

Of course, there are plenty of differences. Those start:

As for use cases — for starters, please note that a large fraction of analytic inquiries are ultimately about people. And when you’re looking at people, there are a whole lot of data sources you can consult. Many are clearly relational; increasingly, however, some are not. What’s more, people are hard to assess and understand, so you may want to take multiple tries at refining your analysis.

So right there you have an argument for flexible investigative or iterative analytics, over multi-structured (and relational) data. And if you think about how to combine information from all those data sources — well, it’s likely that SOME of the analytic steps will be a lot like joins.

That sure sounds like Hadoop/RDBMS integration to me.

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5 Responses to “Hadoop/RDBMS integration: Aster SQL-H and Hadapt”

  1. Notes on Hadoop adoption and trends | DBMS 2 : DataBase Management System Services on October 18th, 2012 10:06 pm

    […] with a 6th client, Tableau); the first 2 whose offerings I’ve actually written about are Teradata Aster and Hadapt. More generally, I’m hearing “Using Hadoop is hard; we’re here to make it easier […]

  2. SQL-Hadoop architectures compared | DBMS 2 : DataBase Management System Services on June 2nd, 2013 6:41 am

    […] SQL-H and Hadapt (October, 2012) […]

  3. DBMS development and other subjects | DBMS 2 : DataBase Management System Services on January 31st, 2014 9:05 am

    […] cardinal rules of DBMS development. That applies to Impala (Cloudera), Stinger (Hortonworks), and Hadapt, among others. Fortunately, the relevant vendors seem to be well aware of this […]

  4. Introduction to Spark, Shark, BDAS and AMPLab | DBMS 2 : DataBase Management System Services on January 31st, 2014 9:06 am

    […] this as a big deal in complex query execution, for example as an aspect of the design of Impala or Hadapt. But it’s perhaps even more important in iterative machine learning algorithms, which seem to […]

  5. Quick notes on Impala | DBMS 2 : DataBase Management System Services on January 31st, 2014 9:07 am

    […] Impala, announced today. Like Hive, Impala turns Hadoop into a basic analytic RDBMS, with similar SQL/Hadoop integration benefits to those of Hadapt. In […]

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