March 26, 2013

Platfora at the time of first GA

Well-resourced Silicon Valley start-ups typically announce their existence multiple times. Company formation, angel funding, Series A funding, Series B funding, company launch, product beta, and product general availability may not be 7 different “news events”, but they’re apt to be at least 3-4. Platfora, no exception to this rule, is hitting general availability today, and in connection with that I learned a bit more about what they are up to.

In simplest terms, Platfora offers exploratory business intelligence against Hadoop-based data. As per last weekend’s post about exploratory BI, a key requirement is speed; and so far as I can tell, any technological innovation Platfora offers relates to the need for speed. Specifically, I drilled into Platfora’s performance architecture on the query processing side (and associated data movement); Platfora also brags of rendering 100s of 1000s of “marks” quickly in HTML5 visualizations, but I haven’t a clue as to whether that’s much of an accomplishment in itself.

Platfora’s marketing suggests it obviates the need for a data warehouse at all; for most enterprises, of course, that is a great exaggeration. But another dubious aspect of Platfora marketing actually serves to understate the product’s merits — Platfora claims to have an “in-memory” product, when what’s really the case is that Platfora’s memory-centric technology uses both RAM and disk to manage larger data marts than could reasonably be fit into RAM alone. Expanding on what I wrote about Platfora when it de-stealthed

Notes on Platfora’s Hadoop ETL (Extract/Transform/Load) include:

*But in a sad comment on Hadoop’s workload management capabilities, Platfora doesn’t expect these features to be much used, at least at first.

Platfora’s aggregation story goes something like this:

As you would expect, Version 1 of the Platfora data store has various limitations, such as:

Naturally, Platfora hopes to fix these issues down the road.

Finally, a few company notes:

Comments

12 Responses to “Platfora at the time of first GA”

  1. Anthony on March 28th, 2013 1:08 pm

    I see a lot of activity from start-up BI and analytics companies like Platfora, Karmasphere, Datameer, etc. But what are the more established “next-gen” BI providers such as Tableau and QlikView doing to address new Hadoop-based use cases?

  2. Curt Monash on March 28th, 2013 9:53 pm

    There may be some assumptions in your question that I don’t share. But anyhow:

    In cases where BI tool/Hive combos don’t get the job done, you can combine a BI tool, an analytic RDBMS, Hadoop/Hive, and suitable ETL (e.g. via the DBMS’ Hadoop connector). See, for example, my posts about Teradata SQL-H (which now is not restricted to Aster).

  3. Justin Langseth on March 29th, 2013 5:19 pm

    So how is this different from the ROLAP vs. MOLAP wars of the mid 1990’s? Slow but flexible RDBMS queries against a DWH equate to today’s slow but infinitely flexible map-reduce jobs against hdfs. New in-memory(sorta) caches like Platfora’s equate to the old MOLAP cubes.

    Haven’t we seen this movie before?

  4. Curt Monash on March 29th, 2013 5:25 pm

    Justin,

    You can use Platfora’s UI to populate it. At a guess, I’d say that was true of client-side MOLAP (e.g. Cognos), but not server-side (e.g. Essbase). Platfora’s incremental refresh sounds pretty smooth as well.

  5. Anthony on March 29th, 2013 5:53 pm

    Thanks Curt. Curious, what assumptions do you not share?

  6. Curt Monash on March 30th, 2013 11:54 am

    The question seemed to draw distinctions that I don’t recognize, as if certain BI tools could extract from Hadoop into a table and others could not.

    Let’s not push this too far. I’m just trying to guess at what was meant.

  7. DW Consult on May 5th, 2013 10:46 pm

    Sounds like Platfora is building what Metamarkets already run on, a cube based in memory structure with visualization. Not sure how it makes hadoop more efficient for large data sets. It is going back to 1990s…..

  8. Curt Monash on May 5th, 2013 11:50 pm

    The general idea of Platfora is indeed a lot like Metamarkets. But you control it (vs. Metamarkets’ SaaS), and the style of BI is different — Tableau-lite for Platfora, va. more traditional in the case of Metamarkets.

  9. The refactoring of everything | DBMS 2 : DataBase Management System Services on July 23rd, 2013 7:17 am

    […] feature proprietary data stores, often memory-centric. Two examples I’ve written about are Platfora and QlikView, but “in-memory BI” goes far beyond those two […]

  10. What matters in investigative analytics? | DBMS 2 : DataBase Management System Services on October 6th, 2013 8:11 am

    […] Usually that’s in the context of analytic DBMS, but it also arises in analytic stacks such as Platfora, Metamarkets or even QlikView, and also in the challenges of making predictive modeling […]

  11. Entity-centric event series analytics | DBMS 2 : DataBase Management System Services on October 19th, 2013 2:00 pm

    […] of my clients are focused on such scenarios, including WibiData, Teradata Aster (e.g. via nPath), Platfora (in the imminent Platfora 3), and others. And so I get involved in naming exercises. The term […]

  12. Necessary complexity | DBMS 2 : DataBase Management System Services on April 19th, 2014 4:17 am

    […] Platfora. […]

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