Three ways Fedex is a metaphor for data integration
It occurs to me that there are three reasons why Federal Express, aka Fedex, is a great metaphor for data integration. Read more
The Continuent Tungsten MySQL replication story
To the consternation of its then-CEO, I wrote very little about my then-client Continuent. However, when I knew Schooner’s recent announcement was coming, I reached out to other MySQL scale-out vendors too. I’ve already posted accordingly about CodeFutures (the dbShards guys) and ScaleBase. Now it’s late-responding Continuent’s turn.
Actually, what I’m mainly going to do is quote a very long email that Continuent’s current CEO/former CTO Robert Hodges sent me, and which I lightly edited. Read more
| Categories: Continuent, Data integration and middleware, dbShards and CodeFutures, MySQL, Open source, Parallelization, Schooner Information Technology | 9 Comments |
Vertica-Hadoop integration
DBMS/Hadoop integration is a confusing subject. My post on the Cloudera/Aster Data partnership awaits some clarification in the comment thread. A conversation with Vertica left me unsure about some Hadoop/Vertica Year 2 details as well, although I’m doing better after a follow-up call. On the plus side, we also covered some rather cool Hadoop/Vertica product futures, and those seemed easier to understand. 🙂
I say “Year 2” because Hadoop/Vertica integration has been going on since last year. Indeed, Vertica says that there are now over 25 users of the Hadoop/Vertica combination and hence Vertica’s Hadoop connector. Vertica is now introducing — for immediate GA — a new version of its Hadoop connector. So far as I understood: 
Read more
| Categories: Analytic technologies, Cloudera, EAI, EII, ETL, ELT, ETLT, Hadoop, MapReduce, Market share and customer counts, SQL/Hadoop integration, Text, Vertica Systems | 6 Comments |
Evidently IBM bought Cast Iron Systems for $190 million
Sequoia told TechCrunch that Cast Iron Systems was acquired for $190 million. That’s a much more successful exit than I thought.
| Categories: Cast Iron Systems, Data integration and middleware, EAI, EII, ETL, ELT, ETLT, IBM and DB2 | 2 Comments |
Some thoughts on the announcement that IBM is buying Netezza
As you’ve probably read, IBM and Netezza announced a deal today for IBM to buy Netezza. I didn’t sit in on the conference call, but I’ve seen the reporting. Naturally, I have some quick thoughts, which I’ve broken up into several sections below:
- Clearing some underbrush.
- Speculation about what IBM/Netezza will do.
- Speculation about alternative acquirers for Netezza.
- Speculation about what IBM/Netezza competitors will do.
The Workday architecture — a new kind of OLTP software stack
One of my coolest company visits in some time was to SaaS (Software as a Service) vendor Workday, Inc., earlier this month. Reasons included:
- Workday has forward-thinking ideas about SaaS enterprise applications and the integration of business intelligence into same.
- Workday has highly innovative ideas in how it manages data.
- Companies founded by Dave Duffield tend to feature smart, likeable people who talk to one pleasantly and forthrightly. Workday is no exception; CTO Stan Swete and the other Workday folks present were a delight to talk with.
- I’d invited Merv Adrian to come along with me. He asked great questions, and I could gather myself a bit despite how sleep-deprived I was for the first part of that trip.
Workday kindly allowed me to post this Workday slide deck. Otherwise, I’ve split out a quick Workday, Inc. company overview into a separate post.
The biggie for me was the data and object management part. Specifically: Read more
Cloudera Enterprise and Hadoop evolution
I talked with Cloudera a couple of weeks ago in connection with the impending release of Cloudera Enterprise. I’d say: Read more
Netezza’s version of EnterpriseDB-based Oracle compatibility
EnterpriseDB has some deplorable business practices (my stories of being screwed by EnterpriseDB have been met by “Well, you’re hardly the only one”). But a couple of more successful DBMS vendors have happily partnered with EnterpriseDB even so, to help pick off Oracle users. IBM’s approach was in the vein of an EnterpriseDB–infused version of SQL handling within DB2.* Netezza just announced an EnterpriseDB-based Netezza Migrator that is rather different.
*The comment threads are the most informative parts of those posts.
I’m a little unclear as to the Netezza Migrator details, not least because Netezza folks don’t seem to care too much about Netezza Migrator themselves. That said, the core ideas of Netezza Migrator are: Read more
| Categories: Data integration and middleware, Data warehousing, Emulation, transparency, portability, EnterpriseDB and Postgres Plus, Netezza, Oracle | 19 Comments |
Flash is coming, well …
I really, really wanted to title this post “Flash is coming in a flash.” That seems a little exaggerated — but only a little.
- Netezza now intends to come out with a flash-based appliance earlier than it originally expected.
- Indeed, Netezza has suspended — by which I mean “scrapped” — prior plans for a RAM-heavy disk-based appliance. It will use a RAM/flash combo instead.*
- Tim Vincent of IBM told me that customers seem ready to adopt solid-state memory. One interesting comment he made is that Flash isn’t really all that much more expensive than high-end storage area networks.
Uptake of solid-state memory (i.e. flash) for analytic database processing will probably stay pretty low in 2010, but in 2011 it should be a notable (b)leading-edge technology, and it should get mainstreamed pretty quickly after that. Read more
| Categories: Data integration and middleware, Data warehousing, IBM and DB2, Memory-centric data management, Netezza, Solid-state memory, Theory and architecture | 4 Comments |
VoltDB finally launches
VoltDB is finally launching today. As is common for companies in sectors I write about, VoltDB — or just “Volt” — has discovered the virtues of embargoes that end 12:01 am. Let’s go straight to the technical highlights:
- VoltDB is based on the H-Store technology, which I wrote about in February, 2009. Most of what I said about H-Store then applies to VoltDB today.
- VoltDB is a no-apologies ACID relational DBMS, which runs entirely in RAM.
- VoltDB has rather limited SQL. (One example: VoltDB can’t do SUMs in SQL.) However, VoltDB guy Tim Callaghan (Mark Callaghan’s lesser-known but nonetheless smart brother) asserts that if you code up the missing functionality, it’s almost as fast as if it were present in the DBMS to begin with, because there’s no added I/O from the handoff between the DBMS and the procedural code. (The data’s in RAM one way or the other.)
- VoltDB’s Big Conceptual Performance Story is that it does away with most locks, latches, logs, etc., and also most context switching.
- In particular, you’re supposed to partition your data and architect your application so that most transactions execute on a single core. When you can do that, you get VoltDB’s performance benefits. To the extent you can’t, you’re in two-phase-commit performance land. (More precisely, you’re doing 2PC for multi-core writes, which is surely a major reason that multi-core reads are a lot faster in VoltDB than multi-core writes.)
- VoltDB has a little less than one DBMS thread per core. When the data partitioning works as it should, you execute a complete transaction in that single thread. Poof. No context switching.
- A transaction in VoltDB is a Java stored procedure. (The early idea of Ruby on Rails in lieu of the Java/SQL combo didn’t hold up performance-wise.)
- Solid-state memory is not a viable alternative to RAM for VoltDB. Too slow.
- Instead, VoltDB lets you snapshot data to disk at tunable intervals. “Continuous” is one of the options, wherein a new snapshot starts being made as soon as the last one completes.
- In addition, VoltDB will also spool a kind of transaction log to the target of your choice. (Obvious choice: An analytic DBMS such as Vertica, but there’s no such connectivity partnership actually in place at this time.)