Open source

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

November 19, 2012

Couchbase 2.0

My clients at Couchbase checked in.

The big changes in Couchbase 2.0 versus the previous (1.8.x) version are:

Couchbase 2.0 is upwards-compatible with prior versions of Couchbase (and hence with Memcached), but not with CouchDB.

Technology notes on Couchbase 2.0 include: Read more

November 1, 2012

More on Cloudera Impala

What I wrote before about Cloudera Impala was quite incomplete. After a followup call, I now feel I have a better handle on the whole thing.

First, some basics:

The general technical idea of Impala is:

Read more

October 31, 2012

Notes and comments — October 31, 2012

Time for another catch-all post. First and saddest — one of the earliest great commenters on this blog, and a beloved figure in the Boston-area database community, was Dan Weinreb, whom I had known since some Symbolics briefings in the early 1980s. He passed away recently, much much much too young. Looking back for a couple of examples — even if you’ve never heard of him before, I see that Dan ‘s 2009 comment on Tokutek is still interesting today, and so is a post on his own blog disagreeing with some of my choices in terminology.

Otherwise, in no particular order:

1. Chris Bird is learning MongoDB. As is common for Chris, his comments are both amusing and enlightening.

2. When I relayed Cloudera’s comments on Hadoop adoption, I left out a couple of categories. One Cloudera called “mobile”; when I probed, that was about HBase, with an example being messaging apps.

The other was “phone home” — i.e., the ingest of machine-generated data from a lot of different devices. This is something that’s obviously been coming for several years — but I’m increasingly getting the sense that it’s actually arrived.

Read more

October 24, 2012

Quick notes on Impala

Edit: There is now a follow-up post on Cloudera Impala with substantially more detail.

In my world it’s possible to have a hasty 2-hour conversation, and that’s exactly what I had with Cloudera last week. We touched on hardware and general adoption, but much of the conversation was about Cloudera Impala, announced today. Like Hive, Impala turns Hadoop into a basic analytic RDBMS, with similar SQL/Hadoop integration benefits to those of Hadapt. In particular:

Beyond that: Read more

August 6, 2012

Notes, links and comments August 6, 2012

I haven’t done a notes/link/comments post for a while. Time for a little catch-up.

1. MySQL now has a memcached integration story. I haven’t checked the details. The MySQL team is pretty hard to talk with, due to the heavy-handedness of Oracle’s analyst relations.

2. The Large Hadron Collider offers some serious numbers, including:

3. One application area we don’t talk about much for analytic technologies is education. However: Read more

July 15, 2012

Memory-centric data management when locality matters

Ron Pressler of Parallel Universe/SpaceBase pinged me about a data grid product he was open sourcing, called Galaxy. The idea is that a distributed RAM grid will allocate data, not randomly or via consistent hashing, but rather via a locality-sensitive approach. Notes include:

The whole thing is discussed in considerable detail in a blog post and a especially in a Hacker News comment thread. There’s also an error-riddled TechCrunch article. 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

June 25, 2012

Why I’m so forward-leaning about Hadoop features

In my recent series of Hadoop posts, there were several cases where I had to choose between recommending that enterprises:

I favored the more advanced features each time. Here’s why.

To a first approximation, I divide Hadoop use cases into two major buckets, only one of which I was addressing with my comments:

1. Analytic data management.* Here I favored features over reliability because they are more important, for Hadoop as for analytic RDBMS before it. When somebody complains about an analytic data store not being ready for prime time, never really working, or causing them to tear their hair out, what they usually mean is that:

Those complaints are much, much, more frequent than “It crashed”. So it was for Netezza, DATAllegro, Greenplum, Aster Data, Vertica, Infobright, et al. So it also is for Hadoop. And how does one address those complaints? By performance and feature enhancements, of the kind that the Hadoop community is introducing at high speed. Read more

June 19, 2012

Notes on HBase 0.92

This is part of a four-post series, covering:

As part of my recent round of Hadoop research, I talked with Cloudera’s Todd Lipcon. Naturally, one of the subjects was HBase, and specifically HBase 0.92. I gather that the major themes to HBase 0.92 are:

HBase coprocessors are Java code that links straight into HBase. As with other DBMS extensions of the “links straight into the DBMS code” kind,* HBase coprocessors seem best suited for very sophisticated users and third parties.** Evidently, coprocessors have already been used to make HBase security more granular — role-based, per-column-family/per-table, etc. Further, Todd thinks coprocessors could serve as a good basis for future HBase enhancements in areas such as aggregation or secondary indexing. Read more

June 19, 2012

“Enterprise-ready Hadoop”

This is part of a four-post series, covering:

The posts depend on each other in various ways.

Cloudera, Hortonworks, and MapR all claim, in effect, “Our version of Hadoop is enterprise-ready, unlike those other guys’.” I’m dubious.

That said, “enterprise-ready Hadoop” really is an important topic.

So what does it mean for something to be “enterprise-ready”, in whole or in part? Common themes in distinguishing between “enterprise-class” and other software include:

For Hadoop, as for most things, these concepts overlap in many ways. Read more

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