Theory and architecture

Analysis of design choices in databases and database management systems. Related subjects include:

October 3, 2016

Notes on the transition to the cloud

1. The cloud is super-hot. Duh. And so, like any hot buzzword, “cloud” means different things to different marketers. Four of the biggest things that have been called “cloud” are:

Further, there’s always the idea of hybrid cloud, in which a vendor peddles private cloud systems (usually appliances) running similar technology stacks to what they run in their proprietary public clouds. A number of vendors have backed away from such stories, but a few are still pushing it, including Oracle and Microsoft.

This is a good example of Monash’s Laws of Commercial Semantics.

2. Due to economies of scale, only a few companies should operate their own data centers, aka true on-prem(ises). The rest should use some combination of colo, SaaS, and public cloud.

This fact now seems to be widely understood.

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September 6, 2016

“Real-time” is getting real

I’ve been an analyst for 35 years, and debates about “real-time” technology have run through my whole career. Some of those debates are by now pretty much settled. In particular:

A big issue that does remain open is: How fresh does data need to be? My preferred summary answer is: As fresh as is needed to support the best decision-making. I think that formulation starts with several advantages:

Straightforward applications of this principle include: 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.

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August 7, 2016

Notes on DataStax and Cassandra

I visited DataStax on my recent trip. That was a tipping point leading to my recent discussions of NoSQL DBAs and misplaced fear of vendor lock-in. But of course I also learned some things about DataStax and Cassandra themselves.

On the customer side:

Customers in large numbers want cloud capabilities, as a potential future if not a current need.

One customer example was a large retailer, who in the past was awful at providing accurate inventory information online, but now uses Cassandra for that. DataStax brags that its queries come back in 20 milliseconds, but that strikes me as a bit beside the point; what really matters is that data accuracy has gone from “batch” to some version of real-time. Also, Microsoft is a DataStax customer, using Cassandra (and Spark) for the Office 365 backend, or at least for the associated analytics.

Per Patrick McFadin, the four biggest things in DataStax Enterprise 5 are: 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:

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January 22, 2016

Cloudera in the cloud(s)

Cloudera released Version 2 of Cloudera Director, which is a companion product to Cloudera Manager focused specifically on the cloud. This led to a discussion about — you guessed it! — Cloudera and the cloud.

Making Cloudera run in the cloud has three major aspects:

Features new in this week’s release of Cloudera Director include:

I.e., we’re talking about some pretty basic/checklist kinds of things. Cloudera Director is evidently working for Amazon AWS and Google GCP, and planned for Windows Azure, VMware and OpenStack.

As for porting, let me start by noting: Read more

December 31, 2015

Oracle as the new IBM — has a long decline started?

When I find myself making the same observation fairly frequently, that’s a good impetus to write a post based on it. And so this post is based on the thought that there are many analogies between:

And when you look at things that way, Oracle seems to be swimming against the tide.

Drilling down, there are basically three things that can seriously threaten Oracle’s market position:

Oracle’s decline, if any, will be slow — but I think it has begun.


Oracle/IBM analogies

There’s a clear market lead in the core product category. IBM was dominant in mainframe computing. While not as dominant, Oracle is definitely a strong leader in high-end OTLP/mixed-use (OnLine Transaction Processing) RDBMS.

That market lead is even greater than it looks, because some of the strongest competitors deserve asterisks. Many of IBM’s mainframe competitors were “national champions” — Fujitsu and Hitachi in Japan, Bull in France and so on. Those were probably stronger competitors to IBM than the classic BUNCH companies (Burroughs, Univac, NCR, Control Data, Honeywell).

Similarly, Oracle’s strongest direct competitors are IBM DB2 and Microsoft SQL Server, each of which is sold primarily to customers loyal to the respective vendors’ full stacks. SAP is now trying to play a similar game.

The core product is stable, secure, richly featured, and generally very mature. Duh.

The core product is complicated to administer — which provides great job security for administrators. IBM had JCL (Job Control Language). Oracle has a whole lot of manual work overseeing indexes. In each case, there are many further examples of the point. Edit: A Twitter discussion suggests the specific issue with indexes has been long fixed.

Niche products can actually be more reliable than the big, super-complicated leader. Tandem Nonstop computers were super-reliable. Simple, “embeddable” RDBMS — e.g. Progress or SQL Anywhere — in many cases just work. Still, if you want one system to run most of your workload 24×7, it’s natural to choose the category leader. Read more

December 10, 2015

Readings in Database Systems

Mike Stonebraker and Larry Ellison have numerous things in common. If nothing else:

I mention the latter because there’s a new edition of Readings in Database Systems, aka the Red Book, available online, courtesy of Mike, Joe Hellerstein and Peter Bailis. Besides the recommended-reading academic papers themselves, there are 12 survey articles by the editors, and an occasional response where, for example, editors disagree. Whether or not one chooses to tackle the papers themselves — and I in fact have not dived into them — the commentary is of great interest.

But I would not take every word as the gospel truth, especially when academics describe what they see as commercial market realities. In particular, as per my quip in the first paragraph, the data warehouse market has not yet gone to the extremes that Mike suggests,* if indeed it ever will. And while Joe is close to correct when he says that the company Essbase was acquired by Oracle, what actually happened is that Arbor Software, which made Essbase, merged with Hyperion Software, and the latter was eventually indeed bought by the giant of Redwood Shores.**

*When it comes to data warehouse market assessment, Mike seems to often be ahead of the trend.

**Let me interrupt my tweaking of very smart people to confess that my own commentary on the Oracle/Hyperion deal was not, in retrospect, especially prescient.

Mike pretty much opened the discussion with a blistering attack against hierarchical data models such as JSON or XML. To a first approximation, his views might be summarized as:  Read more

November 19, 2015

The questionably named Cloudera Navigator Optimizer

I only have mixed success at getting my clients to reach out to me for messaging advice when they’re introducing something new. Cloudera Navigator Optimizer, which is being announced along with Cloudera 5.5, is one of my failures in that respect; I heard about it for the first time Tuesday afternoon. I hate the name. I hate some of the slides I saw. But I do like one part of the messaging, namely the statement that this is about “refactoring” queries.

All messaging quibbles aside, I think the Cloudera Navigator Optimizer story is actually pretty interesting, and perhaps not just to users of SQL-on-Hadoop technologies such as Hive (which I guess I’d put in that category for simplicity) or Impala. As I understand Cloudera Navigator Optimizer:

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November 19, 2015

CDH 5.5

I talked with Cloudera shortly ahead of today’s announcement of Cloudera 5.5. Much of what we talked about had something or other to do with SQL data management. Highlights include:

While I had Cloudera on the phone, I asked a few questions about Impala adoption, specifically focused on concurrency. There was mention of: Read more

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