February 18, 2015

Greenplum is being open sourced

While I don’t find the Open Data Platform thing very significant, an associated piece of news seems cooler — Pivotal is open sourcing a bunch of software, with Greenplum as the crown jewel. Notes on that start:

Greenplum, let us recall, is a pretty decent MPP (Massively Parallel Processing) analytic RDBMS. Various aspects of it were oversold at various times, and I’ve never heard that they actually licked concurrency. But Greenplum has long had good SQL coverage and petabyte-scale deployments and a columnar option and some in-database analytics and so on; i.e., it’s legit. When somebody asks me about open source analytic RDBMS to consider, I expect Greenplum to consistently be on the short list.

Further, the low-cost alternatives for analytic RDBMS are adding up. Read more

December 10, 2014

A few numbers from MapR

MapR put out a press release aggregating some customer information; unfortunately, the release is a monument to vagueness. Let me start by saying:

Anyhow, the key statement in the MapR release is:

… the number of companies that have a paid subscription for MapR now exceeds 700.

Unfortunately, that includes OEM customers as well as direct ones; I imagine MapR’s direct customer count is much lower.

In one gesture to numerical conservatism, MapR did indicate by email that it counts by overall customer organization, not by department/cluster/contract (i.e., not the way Hortonworks does). Read more

December 7, 2014

Notes on the Hortonworks IPO S-1 filing

Given my stock research experience, perhaps I should post about Hortonworks’ initial public offering S-1 filing. :) For starters, let me say:

And, perhaps of interest only to me — there are approximately 50 references to YARN in the Hortonworks S-1, but only 1 mention of Tez.

Read more

October 22, 2014

Snowflake Computing

I talked with the Snowflake Computing guys Friday. For starters:

Much of the Snowflake story can be summarized as cloud/elastic/simple/cheap.*

*Excuse me — inexpensive. Companies rarely like their products to be labeled as “cheap”.

In addition to its purely relational functionality, Snowflake accepts poly-structured data. Notes on that start:

I don’t know enough details to judge whether I’d call that an example of schema-on-need.

A key element of Snowflake’s poly-structured data story seems to be lateral views. I’m not too clear on that concept, but I gather: Read more

October 13, 2014

Context for Cloudera

Hadoop World/Strata is this week, so of course my clients at Cloudera will have a bunch of announcements. Without front-running those, I think it might be interesting to review the current state of the Cloudera product line. Details may be found on the Cloudera product comparison page. Examining those details helps, I think, with understanding where Cloudera does and doesn’t place sales and marketing focus, which given Cloudera’s Hadoop market stature is in my opinion an interesting thing to analyze.

So far as I can tell (and there may be some errors in this, as Cloudera is not always accurate in explaining the fine details):

In analyzing all this, I’m focused on two particular aspects:

Read more

April 30, 2014

Hardware and storage notes

My California trip last week focused mainly on software — duh! — but I had some interesting hardware/storage/architecture discussions as well, especially in the areas of:

I also got updated as to typical Hadoop hardware.

If systems are designed at the whole-rack level or higher, then there can be much more flexibility and efficiency in terms of mixing and connecting CPU, RAM and storage. The Google/Facebook/Amazon cool kids are widely understood to be following this approach, so others are naturally considering it as well. My most interesting of several mentions of that point was when I got the chance to talk with Berkeley computer architecture guru Dave Patterson, who’s working on plans for 100-petabyte/terabit-networking kinds of systems, for usage after 2020 or so. (If you’re interested, you might want to contact him; I’m sure he’d love more commercial sponsorship.)

One of Dave’s design assumptions is that Moore’s Law really will end soon (or at least greatly slow down), if by Moore’s Law you mean that every 18 months or so one can get twice as many transistors onto a chip of the same area and cost than one could before. However, while he thinks that applies to CPU and RAM, Dave thinks flash is an exception. I gathered that he thinks the power/heat reasons for Moore’s Law to end will be much harder to defeat than the other ones; note that flash, because of what it’s used for, has vastly less power running through it than CPU or RAM do.

Read more

April 17, 2014

MongoDB is growing up

I caught up with my clients at MongoDB to discuss the recent MongoDB 2.6, along with some new statements of direction. The biggest takeaway is that the MongoDB product, along with the associated MMS (MongoDB Management Service), is growing up. Aspects include:

Read more

February 2, 2014

Some stuff I’m thinking about (early 2014)

From time to time I like to do “what I’m working on” posts. From my recent blogging, you probably already know that includes:

Other stuff on my mind includes but is not limited to:

1. Certain categories of buying organizations are inherently leading-edge.

Fine. But what really intrigues me is when more ordinary enterprises also put leading-edge technologies into production. I pester everybody for examples of that.

Read more

December 5, 2013

Vertica 7

It took me a bit of time, and an extra call with Vertica’s long-time R&D chief Shilpa Lawande, but I think I have a decent handle now on Vertica 7, code-named Crane. The two aspects of Vertica 7 I find most interesting are:

Other Vertica 7 enhancements include:

Overall, two recurring themes in our discussion were:

Read more

November 24, 2013

Thoughts on SaaS

Generalizing about SaaS (Software as a Service) is hard. To prune some of the confusion, let’s start by noting:

For smaller enterprises, the core outsourcing argument is compelling. How small? Well:

So except for special cases, an enterprise with less than $100 million or so in revenue may have trouble affording on-site data processing, at least at a mission-critical level of robustness. It may well be better to use NetSuite or something like that, assuming needed features are available in SaaS form.*

Read more

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