Open source

Discussion of relational database management systems that are offered through some version of open source licensing. Related subjects include:

June 16, 2017

Generally available Kudu

I talked with Cloudera about Kudu in early May. Besides giving me a lot of information about Kudu, Cloudera also helped confirm some trends I’m seeing elsewhere, including:

Now let’s talk about Kudu itself. As I discussed at length in September 2015, Kudu is:

Kudu’s adoption and roll-out story starts: Read more

March 12, 2017

Introduction to SequoiaDB and SequoiaCM

For starters, let me say:


Unfortunately, SequoiaDB has not captured a lot of detailed information about unpaid open source production usage.

Read more

December 18, 2016

Introduction to and CrateDB and CrateDB basics include:

In essence, CrateDB is an open source and less mature alternative to MemSQL. The opportunity for MemSQL and CrateDB alike exists in part because analytic RDBMS vendors didn’t close it off.

CrateDB’s not-just-relational story starts:

Read more

November 23, 2016

MongoDB 3.4 and “multimodel” query

“Multimodel” database management is a hot new concept these days, notwithstanding that it’s been around since at least the 1990s. My clients at MongoDB of course had to join the train as well, but they’ve taken a clear and interesting stance:

When I pointed out that it would make sense to call this “multimodel query” — because the storage isn’t “multimodel” at all — they quickly agreed.

To be clear: While there are multiple ways to read data in MongoDB, there’s still only one way to write it. Letting that sink in helps clear up confusion as to what about MongoDB is or isn’t “multimodel”. To spell that out a bit further: Read more

August 28, 2016

Are analytic RDBMS and data warehouse appliances obsolete?

I used to spend most of my time — blogging and consulting alike — on data warehouse appliances and analytic DBMS. Now I’m barely involved with them. The most obvious reason is that there have been drastic changes in industry structure:

Simply reciting all that, however, begs the question of whether one should still care about analytic RDBMS at all.

My answer, in a nutshell, is:

Analytic RDBMS — whether on premises in software, in the form of data warehouse appliances, or in the cloud – are still great for hard-core business intelligence, where “hard-core” can refer to ad-hoc query complexity, reporting/dashboard concurrency, or both. But they aren’t good for much else.

Read more

August 21, 2016

Introduction to data Artisans and Flink

data Artisans and Flink basics start:

Like many open source projects, Flink seems to have been partly inspired by a Google paper.

To this point, data Artisans and Flink have less maturity and traction than Databricks and Spark. For example:  Read more

August 21, 2016

More about Databricks and Spark

Databricks CEO Ali Ghodsi checked in because he disagreed with part of my recent post about Databricks. Ali’s take on Databricks’ position in the Spark world includes:

Ali also walked me through customer use cases and adoption in wonderful detail. In general:

The story on those sectors, per Ali, is:  Read more

July 19, 2016

Notes on vendor lock-in

Vendor lock-in is an important subject. Everybody knows that. But few of us realize just how complicated the subject is, nor how riddled it is with paradoxes. Truth be told, I wasn’t fully aware either. But when I set out to write this post, I found that it just kept growing longer.

1. The most basic form of lock-in is:

2. Enterprise vendor standardization is closely associated with lock-in. The core idea is that you have a mandate or strong bias toward having different apps run over the same platforms, because:

3. That last point is double-edged; you have more power over suppliers to whom you give more business, but they also have more power over you. The upshot is often an ELA (Enterprise License Agreement), which commonly works:

Read more

July 19, 2016

Notes from a long trip, July 19, 2016

For starters:

A running list of recent posts is:

Subjects I’d like to add to that list include:

Read more

January 25, 2016

Kafka and Confluent

For starters:

At its core Kafka is very simple:

So it seems fair to say:

Read more

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