Analysis of technologies that accelerate database management via caching. Related subjects include:

September 8, 2013

Layering of database technology & DBMS with multiple DMLs

Two subjects in one post, because they were too hard to separate from each other

Any sufficiently complex software is developed in modules and subsystems. DBMS are no exception; the core trinity of parser, optimizer/planner, and execution engine merely starts the discussion. But increasingly, database technology is layered in a more fundamental way as well, to the extent that different parts of what would seem to be an integrated DBMS can sometimes be developed by separate vendors.

Major examples of this trend — where by “major” I mean “spanning a lot of different vendors or projects” — include:

Other examples on my mind include:

And there are several others I hope to blog about soon, e.g. current-day PostgreSQL.

In an overlapping trend, DBMS increasingly have multiple data manipulation APIs. Examples include:  Read more

January 12, 2013

Introduction to NuoDB

NuoDB has an interesting NewSQL story. NuoDB’s core design goals seem to be:

Read more

January 7, 2013

Introduction to GenieDB

GenieDB is one of the newer and smaller NewSQL companies. GenieDB’s story is focused on wide-area replication and uptime, coupled to claims about ease and the associated low TCO (Total Cost of Ownership).

GenieDB is in my same family of clients as Cirro.

The GenieDB product is more interesting if we conflate the existing GenieDB Version 1 and a soon-forthcoming (mid-year or so) Version 2. On that basis:

The heart of the GenieDB story is probably wide-area replication. Specifics there include:  Read more

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

September 7, 2012

Integrated internet system design

What are the central challenges in internet system design? We probably all have similar lists, comprising issues such as scale, scale-out, throughput, availability, security, programming ease, UI, or general cost-effectiveness. Screw those up, and you don’t have an internet business.

Much new technology addresses those challenges, with considerable success. But the success is usually one silo at a time — a short-request application here, an analytic database there. When it comes to integration, unsolved problems abound.

The top integration and integration-like challenges for me, from a practical standpoint, are:

Other concerns that get mentioned include:

Let’s skip those latter issues for now, focusing instead on the first four.

Read more

August 20, 2012

In-memory, (hybrid) memory-centric DBMS — three analytic glossary draft entries

These are three closely-related draft entries for the DBMS2 analytic glossary. Please comment with any ideas you have for their improvement!

1. We coined the term memory-centric data management to comprise several kinds of technology that manage data in RAM (Random Access Memory), including:

Related link

2. An in-memory DBMS is a DBMS designed under the assumption that substantially all database operations will be performed in RAM (Random Access Memory). Thus, in-memory DBMS form a subcategory of memory-centric data management systems.

Ways in which in-memory DBMS are commonly different from those that query and update persistent storage include: 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

June 14, 2012

Workday update

In August 2010, I wrote about Workday’s interesting technical architecture, highlights of which included:

I caught up with Workday recently, and things have naturally evolved. Most of what we talked about (by my choice) dealt with data management, business intelligence, and the overlap between the two.

It is now reasonable to say that Workday’s servers fall into at least seven tiers, although we talked mainly about five that work together as a kind of giant app/database server amalgamation. The three that do noteworthy data management can be described as:

Two other Workday server tiers may be described as: Read more

April 7, 2012

Many kinds of memory-centric data management

I’m frequently asked to generalize in some way about in-memory or memory-centric data management. I can start:

Getting more specific than that is hard, however, because:

Consider, for example, some of the in-memory data management ideas kicking around. Read more

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