Greenplum

Analysis of data warehouse DBMS vendor Greenplum. 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:

Is free of charge, although you can buy support.
Has no restrictions on use, production or otherwise.
Has no restrictions on database size.
Is closed-source.

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:

General-purpose open-source DBMS, such as PostgreSQL and MySQL (lacking analytic DBMS performance and features)
Infobright Community Edition (the other best choice – Infobright’s commercial sales success indicates the solidity of Infobright’s technology)
Rough research-project code and other other questionable open source offerings
Crippleware from other commercial analytic DBMS vendors (e.g., Teradata)

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

The ability to scale out queries across all cores in your box (and no, pgpool is not a serious alternative)
Storage alternatives such as columnar (I am told that EnterpriseDB recently stopped funding a project for a PostgreSQL columnar option)

Categories: Analytic technologies, Data warehousing, EnterpriseDB and Postgres Plus, Greenplum, Infobright, Open source, PostgreSQL, Pricing, Scientific research

9 Comments

October 18, 2009

Greenplum customer notes

In a briefing about a forthcoming product announcement, Greenplum threw in a slide saying:

Greenplum is getting 12-15 new (paying) customers per quarter, all of whom it fondly refers to as “Tier 1″ enterprises.
Greenplum will hit the 100+ customer mark this quarter (thus joining Vertica and Infobright).
<10% of Greenplum business is now “influenced” by Sun hardware.

I asked Ben Werther to unpack that last claim for me. He quickly noted that it wasn’t his slide, but rather had been put together by colleagues. That said:

As of the past quarter or two, <10% of Greenplum’s sales activity is on Sun, which works out to maybe one sale per quarter and at most a small number of sales cycles. (That’s down from from 50%+ not that long ago.)
Most Greenplum business is now on HP or Dell equipment. Some is on IBM. There are some interesting sales cycles on Cisco’s new UCS (Unified Computing System) blades, but no closed deals yet. EMC seems to be part of the Cisco story.

No doubt part of the reason for the move away from Sun equipment is the impending Oracle acquisition. Another may be that the Greenplum/Sun appliance is somewhat underpowered. E.g., without particularly high levels of compression, eBay puts over 60 terabytes of data on each Greenplum node, which probably isn’t ideal from the standpoint of query performance.

Greenplum also says that 50% or so of sales are subscription-priced, rather than perpetual-licensed. I don’t have a sense for how long that’s been going on. (Edit: Ben Werther tells me this has been true for over a year.)

Categories: Data warehouse appliances, Data warehousing, Greenplum, Market share, Pricing

1 Comment

October 18, 2009

Three big myths about MapReduce

Once again, I find myself writing and talking a lot about MapReduce. But I suspect that MapReduce-related conversations would go better if we overcame three fairly common MapReduce myths:

MapReduce is something very new
MapReduce involves strict adherence to the Map-Reduce programming paradigm
MapReduce is a single technology

Categories: Analytic technologies, Aster Data, Cloudera, Data warehousing, Google, Greenplum, Hadoop, Log analysis, MapReduce, Michael Stonebraker, Parallelization, Web analytics

11 Comments

October 14, 2009

Greenplum is going hybrid columnar as well

Over the past summer, Vertica, VectorWise, and Oracle all announced flavors of hybrid row/columnar storage. Now it’s Greenplum’s turn. Greenplum is actually offering true columnar storage, as opposed to Oracle’s PAX-like scheme — and also as opposed to the kind of Frankencolumn storage Daniel Abadi decries. For example, you don’t have to do a join to retrieve multiple columns; you just ask for them and there they are. Similarly, Greenplum doesn’t maintain explicit row IDs – whether in row-oriented or column-oriented append-only storage – relying instead on block-level header information. Read more

Categories: Analytic technologies, Columnar database management, Data warehousing, Database compression, Greenplum, Theory and architecture

8 Comments

June 25, 2009

My current customer list among the analytic DBMS specialists

(This is an updated version of an August, 2008 post.)

One of my favorite pages on the Monash Research website is the list of many current and a few notable past customers. (Another favorite page is the one for testimonials.) For a variety of reasons, I won’t undertake to be more precise about my current customer list than that. But I don’t think it would hurt anything to list the analytic/data warehouse DBMS/appliance specialists in the group. They are:

Aster Data
Greenplum
Infobright
Kickfire
Kognitio
Microsoft
Netezza (my biggest client this year, probably, because of all the Enzee Universe appearances)
Sybase
Teradata
Vertica
Attivio, which may or may not be construed as being in the analytic DBMS business
Clearpace, ditto

All of those are Monash Advantage members.

If you care about all this, you may also be interested in the rest of my standards and disclosures.

Categories: About this blog, Aster Data, Data warehousing, Greenplum, Infobright, Kickfire, Microsoft and SQL*Server, Netezza, Sybase, Teradata, Vertica Systems

4 Comments

June 9, 2009

Aster Data sticks by its SQL/MapReduce guns

Aster Data continues to think that MapReduce, integrated with SQL, is an important technology. For example:

Aster announced today that it’s providing .NET support for SQL/MapReduce. Perhaps not coincidentally, Aster’s biggest customer is MySpace, which is apparently a big Microsoft shop. (And MySpace parent Fox Interactive Media is a SQL/MapReduce fan, albeit running on Greenplum.)
Aster generally puts more emphasis on MapReduce than SQL/MapReduce rival Greenplum. That’s a non-trivial comparison, because Greenplum is making progress in SQL/MapReduce itself.
When talking with Aster folks, I can’t get them to shut up hear a lot about SQL/MapReduce.

I was a big fan of SQL/MapReduce when it was first announced last August. Notwithstanding persuasive examples favoring pure DBMS or pure MapReduce over DBMS/MapReduce integration, I continue to think the SQL/MapReduce idea has great potential. But I do wish more successful production examples would become visible …

Categories: Analytic technologies, Aster Data, Data warehousing, Fox and MySpace, Greenplum, MapReduce, Parallelization

4 Comments

June 8, 2009

Per-terabyte pricing

Software-only DBMS vendors sometimes price per terabyte of user data. Vertica’s list price is $100K/TB. Greenplum’s list price is $70K/TB. In practice, both offer substantial discounts, especially at higher volumes. In both cases, this means raw data, uncompressed, without counting indexes or temp space.

Client experience teaches me that this definition is easy to forget, so let me reemphasize the key point:

Per-terabyte pricing is based on a calculated figure. Per-terabyte pricing is not based on the current disk space used by your database when managed by the DBMS you are replacing.

There’s at least one important difference in how Vertica and Greenplum calculate database size. No matter how many times you copy the data, Vertica only charges you for it once.* But if you spin out data marts and recopy data into it — as Greenplum rightly encourages you to do — Greenplum wants to be paid for each copy. Similarly, Vertica charges only for deployment, and not for test or development; I didn’t remember to ask what Greenplum’s policies are in those regards. (Edit: Greenplum says in a comment below that it doesn’t charge for test or development data either.)

*That policy is a great fit with Vertica’s performance recommendation that you should store columns in different sort orders, perhaps an average of two copies per column.

Categories: Columnar database management, Data warehousing, Greenplum, Pricing, Vertica Systems

5 Comments

June 8, 2009

Greenplum blogs about some customers

I’ve written some about Greenplum’s customers at eBay and Fox Interactive Media. But as I recently grumped, I’m not in the mood right now to write much about other Greenplum customers. Fortunately, Greenplum has filled the gap itself. Marketing chief Paul Salazar just blogged about a number of other big Greenplum customers. And last month Paul blogged in considerable detail about what he characterizes as an enterprise data warehouse (EDW) conversion — Oracle replacement — at a large pharmaceutical company.

Categories: Application areas, Data warehousing, Greenplum, Oracle

The future of data marts

Greenplum is announcing today a long-term vision, under the name Enterprise Data Cloud (EDC). Key observations around the concept — mixing mine and Greenplum’s together — include:

Data marts aren’t just for performance (or price/performance). They also exist to give individual analysts or small teams control of their analytic destiny.
Thus, it would be really cool if business users could have their own analytic “sandboxes” — virtual or physical analytic databases that they can manipulate without breaking anything else.
In any case, business users want to analyze data when they want to analyze it. It is often unwise to ask business users to postpone analysis until after an enterprise data model can be extended to fully incorporate the new data they want to look at.
Whether or not you agree with that, it’s an empirical fact that enterprises have many legacy data marts (or even, especially due to M&A, multiple legacy data warehouses). Similarly, it’s an empirical fact that many business users have the clout to order up new data marts as well.
Consolidating data marts onto one common technological platform has important benefits.

In essence, Greenplum is pitching the story:

Thesis: Enterprise Data Warehouses (EDWs)
Antithesis: Data Warehouse Appliances
Synthesis: Greenplum’s Enterprise Data Cloud vision

When put that starkly, it’s overstated, not least because

Specialized Analytic DBMS != Data Warehouse Appliance

But basically it makes sense, for two main reasons:

Analysis is performed on all sorts of novel data, from sources far beyond an enterprise’s core transactions. This data neither has to fit nor particularly benefits from being tightly fitted into the core enterprise data model. Requiring it to do so is just an unnecessary and painful bureaucratic delay.
On the other hand, consolidation can be a good idea even when systems don’t particularly interoperate. Data marts, which commonly do in part interoperate with central data stores, have all the more reason to be consolidated onto a central technology platform/stack.