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

December 9, 2012

Amazon Redshift and its implications

Merv Adrian and Doug Henschen both reported more details about Amazon Redshift than I intend to; see also the comments on Doug’s article. I did talk with Rick Glick of ParAccel a bit about the project, and he noted:

“We didn’t want to do the deal on those terms” comments from other companies suggest ParAccel’s main financial take from the deal is an already-reported venture investment.

The cloud-related engineering was mainly around communications, e.g. strengthening error detection/correction to make up for the lack of dedicated switches. In general, Rick seemed more positive on running in the (Amazon) cloud than analytic RDBMS vendors have been in the past.

So who should and will use Amazon Redshift? For starters, I’d say: Read more

October 17, 2012

Hadoop/RDBMS integration: Aster SQL-H and Hadapt

Two of the more interesting approaches for integrating Hadoop and MapReduce with relational DBMS come from my clients at Teradata Aster (via SQL/MR and SQL-H) and Hadapt. In both cases, the story starts:

Of course, there are plenty of differences. Those start: Read more

October 17, 2012

The Teradata Aster Big Analytics Aster/Hadoop appliance

My clients at Teradata are introducing a mix-em/match-em Aster/Hadoop box, officially called the Teradata Aster Big Analytics Appliance. Basics include:

My views on the Teradata Aster Big Analytics Appliance start: Read more

August 27, 2012

Aerospike, the former Citrusleaf

My new clients at Aerospike have a range of minor news to announce:

Mainly, however, they want to call your attention to the fact that they’ve been selling a fast, reliable key-value store, with a number of production references, and want to suggest that other organizations should perhaps buy it as well.

Generally, the Aerospike product story is as I described in two posts last year. At the highest level:

AeroSpike’s three core marketing claims are performance, consistent performance, and uninterrupted operations.

Aerospike technical details start with the expected: 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

July 5, 2012

Introduction to Neo Technology and Neo4j

I’ve been talking some with the Neo Technology/Neo4j guys, including Emil Eifrem (CEO/cofounder), Johan Svensson (CTO/cofounder), and Philip Rathle (Senior Director of Products). Basics include:

Numbers and historical facts include:

Read more

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