October 30, 2009

Aster Data 4.0 and the evolution of “advanced analytic(s) servers”

Since Linda and I are leaving on vacation in a few hours, Aster Data graciously gave me permission to morph its “12:01 am Monday, November 2” embargo into “late Friday night.”

Aster Data is officially announcing the 4.0 release of nCluster. There are two big pieces to this announcement:

In addition, Aster has matured nCluster in various ways, for example cleaning up a performance problem with single-row updates.

Highlights of the Aster “Data-Application Server” story include:

In a compelling proof point for the Aster Data-Application Server’s slickness, Aster has leapfrogged Teradata and Netezza in the extent to which SAS functionality is integrated into Aster’s DBMS. (Aster and SAS both say that you can do full SAS modeling in parallel on Aster, but even so I wouldn’t be surprised to discover there were some parts of SAS’ system that turned out to be exceptions.) Of course, Aster is hardly the only analytic DBMS vendor to have the idea of explicitly enhancing general analytic processing; that’s why we see lots of MapReduce announcements, and it’s also why Teradata enhanced its UDFs (User-Defined Functions) to have some kind of persistent memory.* But I don’t know of anybody else whose approach is quite so elegant and general at this time.

*Unfortunately, I don’t yet know much about Teradata’s UDF enhancements. I neglected to drill down on Global Persistent Memory when it was mentioned a couple of times at Teradata Partners last week, and Teradata was unable to accommodate my request this week for a rapid follow-up briefing on the subject.

Aster’s approach to workload management is similarly stylish. The idea is:

Right now the interface is – well, you’re manipulating a SQL table. A more conventional workload management GUI is slated for the second quarter of 2010.

Discussing subjects such as mirroring and ILM (Information Lifecycle Management) with Aster can be tricky, as Aster uses the word “partition” in confusing ways. Anyhow, Aster has a few different levels of compression, and the ability to apply different levels of compression to different partitions, to change compression levels via ALTER TABLE, and to alter (presumably increase) compression on the fly when doing online backup. Aster is also part of a growing trend to eschew RAID, instead doing mirroring in its own software. (Other examples of this strategy would be Vertica, Oracle Exadata/ASM, and Teradata Fallback.) Prior to nCluster 4.0, this caused a problem, in that the block sizes for mirroring were so large as to create a lag in transactional updating. But Aster says this problem is now solved, and indeed claims that nCluster 4.0 is superior to most rivals in transactional efficiency.

And finally, while I was talking w/ Aster Data anyway, I checked up on cloud and MapReduce customer penetration. The answers were:


9 Responses to “Aster Data 4.0 and the evolution of “advanced analytic(s) servers””

  1. Guy Bayes on October 31st, 2009 3:41 pm

    curious Kurt if you have any details on the particulars on ” leapfrogged Teradata and Netezza in the extent to which SAS functionality is integrated into Aster’s DBMS”

  2. Curt Monash on November 1st, 2009 11:39 am


    See the sentence in parentheses immediately after the sentence that contained the word “leapfrogged”.

  3. Guy Bayes on November 3rd, 2009 4:26 pm

    Maybe a better question would be “what specific pieces of SAS functionality does Aster support that Teradata doesn’t”? “Full SAS Modeling” is a little vague

  4. Aster Data architects application logic with data for speeded-up analytics processing en masse | Dana Gardner’s BriefingsDirect | ZDNet.com on November 3rd, 2009 5:30 pm

    […] the location problem head-on with the announcement this week of Aster Data Version 4.0, (along with Aster nCluster System 4.0), a massively parallel application-data server that allows companies to embed applications inside […]

  5. Boston Big Data Summit keynote outline | DBMS2 -- DataBase Management System Services on November 23rd, 2009 6:35 pm

    […] Data and the cloud actually have relatively little to do with each other, a few exceptions notwithstanding, especially if the data is in a shared-nothing DBMS (as opposed to, say, a […]

  6. TwinFin(i) – Netezza’s version of a parallel analytic platform | DBMS2 -- DataBase Management System Services on February 22nd, 2010 4:21 am

    […] like Aster Data did in Aster 4.0 and now Aster 4.5, Netezza is announcing a general parallel big data analytic platform strategy. It […]

  7. Infobright’s Release 3.4 | DBMS2 -- DataBase Management System Services on August 18th, 2010 2:19 am

    […] up the last huge gaps in an analytic DBMS product seems have become 4.0; recent examples include Aster Data, Vertica and Greenplum. Infobright seems on track to be another example of that […]

  8. Analytic computing systems, aka analytic platforms | DBMS 2 : DataBase Management System Services on January 24th, 2011 3:37 am

    […] to the SQL engine than a pure UDF framework might be. The two main approaches are MapReduce (e.g. Aster Data) and general C++ libraries (Netezza, […]

  9. Aster Data nCluster 4.5 | DBMS 2 : DataBase Management System Services on March 4th, 2011 5:03 am

    […] Aster is using this week to pre-announce a forthcoming product release, Aster Data nCluster 4.5. Aster is really hanging its identity on “Big Data Analytics” or some variant of that concept, and so the two major named parts of Aster nCluster 4.5 […]

Leave a Reply

Feed: DBMS (database management system), DW (data warehousing), BI (business intelligence), and analytics technology Subscribe to the Monash Research feed via RSS or email:


Search our blogs and white papers

Monash Research blogs

User consulting

Building a short list? Refining your strategic plan? We can help.

Vendor advisory

We tell vendors what's happening -- and, more important, what they should do about it.

Monash Research highlights

Learn about white papers, webcasts, and blog highlights, by RSS or email.