Amazon and its cloud

Analysis of Amazon’s role in database and analytic technology, especially via the S3/EC2 cloud computing initiative. Also covered are SimpleDB and Amazon’s role as a technology user. Related subjects include:

June 19, 2012

Hadoop distributions: CDH 4, HDP 1, Hadoop 2.0, Hadoop 1.0 and all that

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

The posts depend on each other in various ways.

My clients at Cloudera and Hortonworks have somewhat different views as to the maturity of various pieces of Hadoop technology. In particular:

*”CDH” stands, due to some trademarking weirdness, for “Cloudera’s Distribution including Apache Hadoop”. “HDP” stands for “Hortonworks Data Platform”.

Read more

June 16, 2012

Metamarkets’ back-end technology

This is part of a three-post series:

The canonical Metamarkets batch ingest pipeline is a bit complicated.

By “get data read to be put into Druid” I mean:

That metadata is what goes into the MySQL database, which also retains data about shards that have been invalidated. (That part is needed because of the MVCC.)

By “build the data segments” I mean:

When things are being done that way, Druid may be regarded as comprising three kinds of servers: Read more

April 24, 2012

Notes on the Hadoop and HBase markets

I visited my clients at Cloudera and Hortonworks last week, along with scads of other companies. A few of the takeaways were:

May 24, 2011

Quick thoughts on Oracle-on-Amazon

Amazon has a page up for what it calls Amazon RDS for Oracle Database. You can rent Amazon instances suitable for running Oracle, and bring your own license (BYOL), or you can rent a “License Included” instance that includes Oracle Standard Edition One (a cheap version of Oracle that is limited to two sockets).

My quick thoughts start:

Of course, those are all standard observations every time something that’s basically on-premises software is offered in the cloud. They’re only reinforced by the fact that the only Oracle software Amazon can actually license you is a particularly low-end edition.

And Oracle is indeed on-premises software. In particular, Oracle is hard enough to manage when it’s on your premises, with a known hardware configuration; who would want to try to manage a production instance of Oracle in the cloud?

July 6, 2010

Cassandra technical overview

Back in March, I talked with Jonathan Ellis of Rackspace, who runs the Apache Cassandra project. I started drafting a blog post then, but never put it up. Then Jonathan cofounded Riptano, a company to commercialize Cassandra, and so I talked with him again in May. Well, I’m finally finding time to clear my Cassandra/Riptano backlog. I’ll cover the more technical parts below, and the more business- or usage-oriented ones in a companion Cassandra/Riptano post.

Jonathan’s core claims for Cassandra include:

In general, Jonathan positions Cassandra as being best-suited to handle a small number of operations at high volume, throughput, and speed. The rest of what you do, as far as he’s concerned, may well belong in a more traditional SQL DBMS.  Read more

May 2, 2010

Daniel Abadi on NoSQL design tradeoffs

In a thought-provoking post, Daniel Abadi points out NoSQL-related terminological problems similar to the ones I just railed against, and argues

To me, CAP should really be PACELC — if there is a partition (P) how does the system tradeoff between availability and consistency (A and C); else (E) when the system is running as normal in the absence of partitions, how does the system tradeoff between latency (L) and consistency (C)?

and goes on to say

For example, Amazon’s Dynamo (and related systems like Cassandra and SimpleDB) are PA/EL in PACELC — upon a partition, they give up consistency for availability; and under normal operation they give up consistency for lower latency. Giving up C in both parts of PACELC makes the design simpler — once the application is configured to be able to handle inconsistencies, it makes sense to give up consistency for both availability and lower latency.

However, I think Daniel’s improved formulation is still misleading, in at least two ways:

May 1, 2010

Read-your-writes (RYW), aka immediate, consistency

In which we reveal the fundamental inequality of NoSQL, and why NoSQL folks are so negative about joins.

Discussions of NoSQL design philosophies tend to quickly focus in on the matter of consistency. “Consistency”, however, turns out to be a rather overloaded concept, and confusion often ensues.

In this post I plan to address one essential subject, while ducking various related ones as hard as I can. It’s what Werner Vogel of Amazon called read-your-writes consistency (a term to which I was actually introduced by Justin Sheehy of Basho). It’s either identical or very similar to what is sometimes called immediate consistency, and presumably also to what Amazon has recently called the “read my last write” capability of SimpleDB.

This is something every database-savvy person should know about, but most so far still don’t. I didn’t myself until a few weeks ago.

Considering the many different kinds of consistency outlined in the Werner Vogel link above or in the Wikipedia consistency models article — whose names may not always be used in, er, a wholly consistent manner — I don’t think there’s much benefit to renaming read-your-writes consistency yet again. Rather, let’s just call it RYW consistency, come up with a way to pronounce “RYW”, and have done with it. (I suggest “ree-ooh”, which evokes two syllables from the original phrase. Thoughts?)

Definition: RYW (Read-Your-Writes) consistency is achieved when the system guarantees that, once a record has been updated, any attempt to read the record will return the updated value.

Read more

March 12, 2010

Some NoSQL links

I plan to post a few things soon about MongoDB, Cassandra, and NoSQL in general. So I’m poking around a bit reading stuff on the subjects. Here are some links I found. Read more

December 27, 2009

Introduction to Gooddata

Around the end of the Cold War, Esther Dyson took it upon herself to go repeatedly to Eastern Europe and do a lot of rah-rah and catalysis, hoping to spark software and other computer entrepreneurs. I don’t know how many people’s lives she significantly affected – I’d guess it’s actually quite a few – but in any case the number is not zero. Roman Stanek, who has built and sold a couple of software business, cites her as a key influence setting him on his path.

Roman’s latest venture is business intelligence firm Gooddata. Gooddata was founded in 2007 and has been soliciting and getting attention for a while, so I was surprised to learn that Gooddata officially launched just a few weeks ago. Anyhow, some less technical highlights of the Gooddata story include: Read more

May 29, 2009

Sneakernet to the cloud

Recently, Amazon CTO Werner Vogels put up a blog post which suggested that, now and in the future, the best way to get large databases into the cloud is via sneakernet.  In some circumstances, he is surely right. Possible implications include:

But for one-time moves of data sets — sure, sneaker net/snail mail should work just fine.

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