Discussion of NoSQL concepts, products, and vendors.

September 14, 2015

DataStax and Cassandra update

MongoDB isn’t the only company I reached out to recently for an update. Another is DataStax. I chatted mainly with Patrick McFadin, somebody with whom I’ve had strong consulting relationships at a user and vendor both. But Rachel Pedreschi contributed the marvelous phrase “twinkling dashboard”.

It seems fair to say that in most cases:

Those generalities, in my opinion, make good technical sense. Even so, there are some edge cases or counterexamples, such as:

*And so a gas company is doing lightweight analysis on boiler temperatures, which it regards as hot data. :)

While most of the specifics are different, I’d say similar things about MongoDB, Cassandra, or any other NoSQL DBMS that comes to mind: Read more

September 10, 2015

MongoDB update

One pleasure in talking with my clients at MongoDB is that few things are NDA. So let’s start with some numbers:

Also >530 staff, and I think that number is a little out of date.

MongoDB lacks many capabilities RDBMS users take for granted. MongoDB 3.2, which I gather is slated for early November, narrows that gap, but only by a little. Features include:

There’s also a closed-source database introspection tool coming, currently codenamed MongoDB Scout.  Read more

July 7, 2015

Zoomdata and the Vs

Let’s start with some terminology biases:

So when my clients at Zoomdata told me that they’re in the business of providing “the fastest visual analytics for big data”, I understood their choice, but rolled my eyes anyway. And then I immediately started to check how their strategy actually plays against the “big data” Vs.

It turns out that:

*The HDFS/S3 aspect seems to be a major part of Zoomdata’s current story.

Core aspects of Zoomdata’s technical strategy include:  Read more

May 26, 2015

IT-centric notes on the future of health care

It’s difficult to project the rate of IT change in health care, because:

Timing aside, it is clear that health care change will be drastic. The IT part of that starts with vastly comprehensive electronic health records, which will be accessible (in part or whole as the case may be) by patients, care givers, care payers and researchers alike. I expect elements of such records to include:

These vastly greater amounts of data cited above will allow for greatly changed analytics.
Read more

April 9, 2015

Which analytic technology problems are important to solve for whom?

I hear much discussion of shortfalls in analytic technology, especially from companies that want to fill in the gaps. But how much do these gaps actually matter? In many cases, that depends on what the analytic technology is being used for. So let’s think about some different kinds of analytic task, and where they each might most stress today’s available technology.

In separating out the task areas, I’ll focus first on the spectrum “To what extent is this supposed to produce novel insights?” and second on the dimension “To what extent is this supposed to be integrated into a production/operational system?” Issues of latency, algorithmic novelty, etc. can follow after those. In particular, let’s consider the tasks: Read more

March 17, 2015

More notes on HBase

1. Continuing from last week’s HBase post, the Cloudera folks were fairly proud of HBase’s features for performance and scalability. Indeed, they suggested that use cases which were a good technical match for HBase were those that required fast random reads and writes with high concurrency and strict consistency. Some of the HBase architecture for query performance seems to be:

Notwithstanding that a couple of those features sound like they might help with analytic queries, the base expectation is that you’ll periodically massage your HBase data into a more analytically-oriented form. For example — I was talking with Cloudera after all — you could put it into Parquet.

2. The discussion of which kinds of data are originally put into HBase was a bit confusing.

OpenTSDB, by the way, likes to store detailed data and aggregates side-by-side, which resembles a pattern I discussed in my recent BI for NoSQL post.

3. HBase supports caching, tiered storage, and so on. Cloudera is pretty sure that it is publicly known (I presume from blog posts or conference talks) that:  Read more

March 15, 2015

BI for NoSQL — some very early comments

Over the past couple years, there have been various quick comments and vague press releases about “BI for NoSQL”. I’ve had trouble, however, imagining what it could amount to that was particularly interesting, with my confusion boiling down to “Just what are you aggregating over what?” Recently I raised the subject with a few leading NoSQL companies. The result is that my confusion was expanded. :) Here’s the small amount that I have actually figured out.

As I noted in a recent post about data models, many databases — in particular SQL and NoSQL ones — can be viewed as collections of <name, value> pairs.

Consequently, a NoSQL database can often be viewed as a table or a collection of tables, except that:

That’s all straightforward to deal with if you’re willing to write scripts to extract the NoSQL data and transform or aggregate it as needed. But things get tricky when you try to insist on some kind of point-and-click. And by the way, that last comment pertains to BI and ETL (Extract/Transform/Load) alike. Indeed, multiple people I talked with on this subject conflated BI and ETL, and they were probably right to do so.

Read more

March 10, 2015

Notes on HBase

I talked with a couple of Cloudera folks about HBase last week. Let me frame things by saying:


Read more

March 10, 2015

Some stuff on my mind, March 10, 2015

I found yesterday’s news quite unpleasant.

And by the way, a guy died a few day ago snorkeling at the same resort I like to go to, evidently doing less risky things than I on occasion have.

So I want to unclutter my mind a bit. Here goes.

1. There are a couple of stories involving Sam Simon and me that are too juvenile to tell on myself, even now. But I’ll say that I ran for senior class president, in a high school where the main way to campaign was via a single large poster, against a guy with enough cartoon-drawing talent to be one of the creators of the Simpsons. Oops.

2. If one suffers from ulcerative colitis as my mother did, one is at high risk of getting colon cancer, as she also did. Mine isn’t as bad as hers was, due to better tolerance for medication controlling the disease. Still, I’ve already had a double-digit number of colonoscopies in my life. They’re not fun. I need another one soon; in fact, I canceled one due to the blizzards.

Pro-tip — never, ever have a colonoscopy without some kind of anesthesia or sedation. Besides the unpleasantness, the lack of meds increases the risk that the colonoscopy will tear you open and make things worse. I learned that the hard way in New York in the early 1980s.

3. Five years ago I wrote optimistically about the evolution of the information ecosystem, specifically using the example of the IT sector. One could argue that I was right. After all:  Read more

February 22, 2015

Data models

7-10 years ago, I repeatedly argued the viewpoints:

Since then, however:

So it’s probably best to revisit all that in a somewhat organized way.

Read more

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