November 8, 2013

Comments on the 2013 Gartner Magic Quadrant for Operational Database Management Systems

The 2013 Gartner Magic Quadrant for Operational Database Management Systems is out. “Operational” seems to be Gartner’s term for what I call short-request, in each case the point being that OLTP (OnLine Transaction Processing) is a dubious term when systems omit strict consistency, and when even strictly consistent systems may lack full transactional semantics. As is usually the case with Gartner Magic Quadrants:

Anyhow:  Read more

October 30, 2013

Glassbeam instantiates a lot of trends

Glassbeam checked in recently, and they turn out to exemplify quite a few of the themes I’ve been writing about. For starters:

Glassbeam basics include:

All Glassbeam customers except one are SaaS/cloud (Software as a Service), and even that one was only offered a subscription (as oppose to perpetual license) price.

So what does Glassbeam’s technology do? Glassbeam says it is focused on “machine data analytics,” specifically for the “Internet of Things”, which it distinguishes from IT logs.* Specifically, Glassbeam sells to manufacturers of complex devices — IT (most of its sales so far ), medical, automotive (aspirational to date), etc. — and helps them analyze “phone home” data, for both support/customer service and marketing kinds of use cases. As of a recent release, the Glassbeam stack can: Read more

August 24, 2013

Hortonworks business notes

Hortonworks did a business-oriented round of outreach, talking with at least Derrick Harris and me. Notes  from my call — for which Rob Bearden didn’t bother showing up — include, in no particular order:

In Hortonworks’ view, Hadoop adopters typically start with a specific use case around a new type of data, such as clickstream, sensor, server log, geolocation, or social.  Read more

August 17, 2013

Aerospike 3

My clients at Aerospike are coming out with their Version 3, and as several of my clients do, have encouraged me to front-run what otherwise would be the Monday embargo.

I encourage such behavior with arguments including:

Aerospike 2’s value proposition, let us recall, was:

… performance, consistent performance, and uninterrupted operations …

  • Aerospike’s consistent performance claims are along the lines of sub-millisecond latency, with 99.9% of responses being within 5 milliseconds, and even a node outage only borking performance for some 10s of milliseconds.
  • Uninterrupted operation is a core Aerospike design goal, and the company says that to date, no Aerospike production cluster has ever gone down.

The major support for such claims is Aerospike’s success in selling to the digital advertising market, which is probably second only to high-frequency trading in its low-latency demands. For example, Aerospike’s CMO Monica Pal sent along a link to what apparently is:

Read more

August 12, 2013

Things I keep needing to say

Some subjects just keep coming up. And so I keep saying things like:

Most generalizations about “Big Data” are false. “Big Data” is a horrific catch-all term, with many different meanings.

Most generalizations about Hadoop are false. Reasons include:

Hadoop won’t soon replace relational data warehouses, if indeed it ever does. SQL-on-Hadoop is still very immature. And you can’t replace data warehouses unless you have the power of SQL.

Note: SQL isn’t the only way to provide “the power of SQL”, but alternative approaches are just as immature.

Most generalizations about NoSQL are false. Different NoSQL products are … different. It’s not even accurate to say that all NoSQL systems lack SQL interfaces. (For example, SQL-on-Hadoop often includes SQL-on-HBase.)

Read more

July 2, 2013

Notes and comments, July 2, 2013

I’m not having a productive week, part of the reason being a hard drive crash that took out early drafts of what were to be last weekend’s blog posts. Now I’m operating from a laptop, rather than my preferred dual-monitor set-up. So please pardon me if I’m concise even by comparison to my usual standards.

*Basic and unavoidable ETL (Extract/Transform/Load) of course excepted.

**I could call that ABC (Always Be Comparing) or ABT (Always Be Testing), but they each sound like – well, like The Glove and the Lions.

June 10, 2013

Where things stand in US government surveillance

Edit: Please see the comment thread below for updates. Please also see a follow-on post about how the surveillance data is actually used.

US government surveillance has exploded into public consciousness since last Thursday. With one major exception, the news has just confirmed what was already thought or known. So where do we stand?

My views about domestic data collection start:

*Recall that these comments are US-specific. Data retention legislation has been proposed or passed in multiple countries to require recording of, among other things, all URL requests, with the stated goal of fighting either digital piracy or child pornography.

As for foreign data: Read more

April 15, 2013

Notes on Teradata systems

Teradata is announcing its new high-end systems, the Teradata 6700 series. Notes on that include:

Teradata is also talking about data integration and best-of-breed systems, with buzzwords such as:

Read more

February 6, 2013

Key questions when selecting an analytic RDBMS

I recently complained that the Gartner Magic Quadrant for Data Warehouse DBMS conflates many use cases into one set of rankings. So perhaps now would be a good time to offer some thoughts on how to tell use cases apart. Assuming you know that you really want to manage your analytic database with a relational DBMS, the first questions you ask yourself could be:

Let’s drill down. Read more

December 12, 2012

Some trends that will continue in 2013

I’m usually annoyed by lists of year-end predictions. Still, a reporter asked me for some, and I found one kind I was comfortable making.

Trends that I think will continue in 2013 include:

Growing attention to machine-generated data. Human-generated data grows at the rate business activity does, plus 0-25%. Machine-generated data grows at the rate of Moore’s Law, also plus 0-25%, which is a much higher total. In particular, the use of remote machine-generated data is becoming increasingly real.

Hadoop adoption. Everybody has the big bit bucket use case, largely because of machine-generated data. Even today’s technology is plenty good enough for that purpose, and hence justifies initial Hadoop adoption. Development of further Hadoop technology, which I post about frequently, is rapid. And so the Hadoop trend is very real.

Application SaaS. The on-premises application software industry has hopeless problems with product complexity and rigidity. Any suite new enough to cut the Gordian Knot is or will be SaaS (Software as a Service).

Newer BI interfaces. Advanced visualization — e.g. Tableau or QlikView — and mobile BI are both hot. So, more speculatively, are “social” BI (Business Intelligence) interfaces.

Price discounts. If you buy software at 50% of list price, you’re probably doing it wrong. Even 25% can be too high.

MySQL alternatives.  NoSQL and NewSQL products often are developed as MySQL alternatives. Oracle has actually done a good job on MySQL technology, but now its business practices are scaring companies away from MySQL commitments, and newer short-request SQL DBMS are ready for use.

Read more

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