Cloud computing

Analysis of cloud computing, especially as applied to database management and analytics. Related subjects include:

October 1, 2012

Notes on the Oracle OpenWorld Sunday keynote

I’m not at Oracle OpenWorld, but as usual that won’t keep me from commenting. My bottom line on the first night’s announcements is:

In particular:

1. At the highest level, my view of Oracle’s strategy is the same as it’s been for several years:

Clayton Christensen’s The Innovator’s Solution teaches us that Oracle should focus on selling a thick stack of technology to its highest-end customers, and that’s exactly what Oracle does focus on.

2. Tonight’s news is closely in line with what Oracle’s Juan Loaiza told me three years ago, especially:

  • Oracle thinks flash memory is the most important hardware technology of the decade, one that could lead to Oracle being “bumped off” if they don’t get it right.
  • Juan believes the “bulk” of Oracle’s business will move over to Exadata-like technology over the next 5-10 years. Numbers-wise, this seems to be based more on Exadata being a platform for consolidating an enterprise’s many Oracle databases than it is on Exadata running a few Especially Big Honking Database management tasks.

3. Oracle is confusing people with its comments on multi-tenancy. I suspect:

4. SaaS (Software as a Service) vendors don’t want to use Oracle, because they don’t want to pay for it.* This limits the potential impact of Oracle’s true multi-tenancy features. Even so: Read more

September 24, 2012

Notes on Hadoop adoption

I successfully resisted telephone consulting while on vacation, but I did do some by email. One was on the oft-recurring subject of Hadoop adoption. I think it’s OK to adapt some of that into a post.

Notes on past and current Hadoop adoption include:

Thoughts on how Hadoop adoption will look going forward include: Read more

July 18, 2012

Clustrix 4.0 and other Clustrix stuff

It feels like time to write about Clustrix, which I last covered in detail in May, 2010, and which is releasing Clustrix 4.0 today. Clustrix and Clustrix 4.0 basics include:

The biggest Clustrix installation seems to be 20 nodes or so. Others seem to have 10+. I presume those disaster recovery customers have 6 or more nodes each. I’m not quite sure how the arithmetic on that all works; perhaps the 125ish count of nodes is a bit low.

Clustrix technical notes include: Read more

June 16, 2012

Metamarkets’ back-end technology

This is part of a three-post series:

The canonical Metamarkets batch ingest pipeline is a bit complicated.

By “get data read to be put into Druid” I mean:

That metadata is what goes into the MySQL database, which also retains data about shards that have been invalidated. (That part is needed because of the MVCC.)

By “build the data segments” I mean:

When things are being done that way, Druid may be regarded as comprising three kinds of servers: Read more

June 16, 2012

Introduction to Metamarkets and Druid

I previously dropped a few hints about my clients at Metamarkets, mentioning that they:

But while they’re a joy to talk with, writing about Metamarkets has been frustrating, with many hours and pages of wasted of effort. Even so, I’m trying again, in a three-post series:

Much like Workday, Inc., Metamarkets is a SaaS (Software as a Service) company, with numerous tiers of servers and an affinity for doing things in RAM. That’s where most of the similarities end, however, as  Metamarkets is a much smaller company than Workday, doing very different things.

Metamarkets’ business is SaaS (Software as a Service) business intelligence, on large data sets, with low latency in both senses (fresh data can be queried on, and the queries happen at RAM speed). As you might imagine, Metamarkets is used by digital marketers and other kinds of internet companies, whose data typically wants to be in the cloud anyway. Approximate metrics for Metamarkets (and it may well have exceeded these by now) include 10 customers, 100,000 queries/day, 80 billion 100-byte events/month (before summarization), 20 employees, 1 popular CEO, and a metric ton of venture capital.

To understand how Metamarkets’ technology works, it probably helps to start by realizing: Read more

June 14, 2012

Workday update

In August 2010, I wrote about Workday’s interesting technical architecture, highlights of which included:

I caught up with Workday recently, and things have naturally evolved. Most of what we talked about (by my choice) dealt with data management, business intelligence, and the overlap between the two.

It is now reasonable to say that Workday’s servers fall into at least seven tiers, although we talked mainly about five that work together as a kind of giant app/database server amalgamation. The three that do noteworthy data management can be described as:

Two other Workday server tiers may be described as: Read more

May 22, 2012

Kognitio’s story today

I had dinner tonight with the Kognitio folks. So far as I can tell:

Kognitio believes that this story is appealing, especially to smaller venture-capital-backed companies, and backs that up with some frieNDA pipeline figures.

Between that success claim and SAP’s HANA figures, it seems that the idea of using an in-memory DBMS to accelerate analytics has legs. This makes sense, as the BI vendors — Qlik Tech excepted — don’t seem to be accomplishing much with their proprietary in-memory alternatives. But I’m not sure that Kognitio would be my first choice to fill that role. Rather, if I wanted to buy an unsuccessful analytic RDBMS to use as an in-memory accelerator, I might consider ParAccel, which is columnar, has an associated compression story, has always had a hybrid memory-centric flavor much as Kognitio has, and is well ahead of Kognitio in the analytic platform derby. That said, I’ll confess to not having talked with or heard much about ParAccel for a while, so I don’t know if they’ve been able maintain technical momentum any more than Kognitio has.

April 24, 2012

Notes on the Hadoop and HBase markets

I visited my clients at Cloudera and Hortonworks last week, along with scads of other companies. A few of the takeaways were:

March 21, 2012

Comments on Oracle’s third quarter 2012 earnings call

Various reporters have asked me about Oracle’s third quarter 2012 earnings conference call. Specific Q&A includes:

What did Oracle do to have its earnings beat Wall Street’s estimates?

Have a bad second quarter and then set Wall Street’s expectations too low for Q3. This isn’t about strong results; it’s about modest expectations.

Can Oracle be a leader in both hardware and software?

Beyond that, please see below.

What about Oracle in the cloud?

MySQL is an important cloud supplier. But Oracle overall hasn’t demonstrated much understanding of what cloud technology and business are all about. An expensive SaaS acquisition here or there could indeed help somewhat, but it seems as if Oracle still has a very long way to go.

Other comments

Other comments on the call, whose transcript is available, include: Read more

November 21, 2011

Analytic trends in 2012: Q&A

As a new year approaches, it’s the season for lists, forecasts and general look-ahead. Press interviews of that nature have already begun. And so I’m working on a trilogy of related posts, all based on an inquiry about hot analytic trends for 2012.

This post is a moderately edited form of an actual interview. Two other posts cover analytic trends to watch (planned) and analytic vendor execution challenges to watch (already up).

Read more

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