Scientific research

Discussion of how database and related technologies are used to support scientific research. Related subjects include:

October 19, 2009

Greenplum Single-Node Edition — sometimes free is a real cool price

Greenplum is announcing today that you can run Greenplum software on a single 8-core commodity server, free. First and foremost, that’s a strong statement that Greenplum wants enterprises to pay it for Greenplum’s parallelization/”private cloud” capabilities. Second, it may be an attractive gift to a variety of folks who want to extract insight from terabyte-scale databases of various kinds.

Greenplum Single-Node Edition:

For those who want free, terabyte-scale data warehousing software, Greenplum Single-Node Edition may be quite appealing, considering that the main available alternatives are:

For example, comparing PostgreSQL-based Greenplum with PostgreSQL itself, Greenplum offers:

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October 10, 2009

How 30+ enterprises are using Hadoop

MapReduce is definitely gaining traction, especially but by no means only in the form of Hadoop. In the aftermath of Hadoop World, Jeff Hammerbacher of Cloudera walked me quickly through 25 customers he pulled from Cloudera’s files. Facts and metrics ranged widely, of course:

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October 10, 2009

Scientific data sharing

I’ve been posting recently about some issues in scientific data management. One topic I haven’t addressed yet is policies around data sharing. Generally:

On the other hand, it’s blindingly obvious that the world as a whole would be better off with widespread scientific data sharing, provided that making data “free” doesn’t significantly undermine scientists’ incentives to capture it in the first place. And institutions such as funding agencies are taking note. Thus:

Scientific data management technology should be suitable for either of the scenarios:

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October 4, 2009

Jacek Becla on issues in scientific data management

Just as Martin Kersten did, Jacek Becla emailed a response to my post on issues in scientific data management. With his permission, I’ve lightly edited his email too, and am posting it below, with some interspersed comments of my own. Read more

October 3, 2009

Martin Kersten on issues in scientific data management

Martin Kersten emailed a response to my post on issues in scientific data management. With his permission, I’ve lightly edited it, and am posting it below. Read more

October 3, 2009

Issues in scientific data management

In the opinion of the leaders of the XLDB and SciDB efforts, key requirements for scientific data management include:

However: Read more

September 13, 2009


Despite a thoughtful heads-up from Daniel Abadi at the time of his original posting about HadoopDB, I’m just getting around to writing about it now. HadoopDB is a research project carried out by a couple of Abadi’s students. Further research is definitely planned. But it seems too early to say that HadoopDB will ever get past the “research and oh by the way the code is open sourced” stage and become a real code line — whether commercialized, open source, or both.

The basic idea of HadoopDB is to put copies of a DBMS at different nodes of a grid, and use Hadoop to parcel work among them. Major benefits when compared with massively parallel DBMS are said to be:

HadoopDB has actually been built with PostgreSQL. That version achieved performance well below that of a commercial DBMS “DBX”, where X=2. Column-store guru Abadi has repeatedly signaled his intention to try out HadoopDB with VectorWise at the nodes instead. (Recall that VectorWise is shared-everything.) It will be interesting to see how that configuration performs.

The real opportunity for HadoopDB, however, in my opinion may lie elsewhere. Read more

September 13, 2009

Fault-tolerant queries

MapReduce/Hadoop fans sometimes raise the question of query fault-tolerance. That is — if a node fails, does the query need to be restarted, or can it keep going? For example, Daniel Abadi et al. trumpet query fault-tolerance as one of the virtues of HadoopDB. Some of the scientists at XLDB spoke of query fault-tolerance as being a good reason to leave 100s or 1000s of terabytes of data in Hadoop-managed file systems.

When we discussed this subject a few months ago in a couple of comment threads, it seemed to be the case that:

This raises an obvious (pair of) question(s) — why and/or when would anybody ever care about query fault-tolerance? Read more

September 12, 2009

Introduction to the XLDB and SciDB projects

Before I write anything else about the overlapping efforts known as XLDB and SciDB, I probably should explain and disambiguate what they are as best I can. XLDB was organized and still is run by guys who want to solve a scientific problem in eXtremely Large DataBase Management, most especially Jacek Becla of SLAC (the organization previously known as Stanford Linear Accelerator Center). Becla’s original motivation was that he needs a DBMS to manage what will be 55 petabytes of raw image data and 100 petabytes of astronomical data total for LSST (Large Synoptic Survey Telescope). Read more

May 13, 2009

IBM System S Streams, aka InfoSphere Streams, aka stream processing, aka “please don’t call it CEP”

IBM has hastily announced System S Streams, a product that was supposed to be called InfoSphere Streams and introduced only in 2010. Apparently, the rush is because senior management wanted to talk about it later this week, and perhaps also because it was implicitly baked into some of IBM’s advertising already. Scrambling ensued. Even so, Jeff Jones and team got to me fast, and briefed me — fairly non-technically, unfortunately, but otherwise how I like it, namely on a harmless embargo and without any NDAs. That’s more than can be said for my clients at Microsoft, who also introduced CEP this week, but I digress …

*Indeed, as I draft this post-Celtics-game, the embargo is already expired.

Marketing aside, IBM System S/InfoSphere Streams is indeed a CEP/stream processing engine + language (with an Eclipse-based development environment). Apparently, IBM’s thinks InfoSphere Streams (if that’s what it winds up being renamed to) is or will be differentiated from other CEP packages in:

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