Announcing new releases of Data Studio family members!
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It’s been just over a month since I last wrote. It’s been pretty busy around here getting ready for the announcement we made today for new releases of some Data Studio products.
Before I get into the details of what we’re announcing, I think I need to clarify exactly what we mean when we say “Data Studio.” Some people still equate Data Studio strictly with the Eclipse-based database development tools. But, really, Data Studio is a family of software designed to deliver an integrated, yet modular, data management environment for all phases of the data management lifecycle, with the goal of increasing collaboration and productivity as data moves through from “requirements to retirement.” And because realizing this vision is a process in itself, we are still in the midst of building out integrations among new and existing tools. This means, the Data Studio family contains a mix of variously branded products. An example of this is Rational Data Architect, which is our key product offering in the data design phase of the data management lifecycle.
One of my colleagues has written a really good developerWorks article that goes into more depth on both the strategic vision of Data Studio as well as how our current offerings address key tasks and roles in a data-centric environment.
So here are the new releases we are announcing today:
· IBM Data Studio Developer 1.2
· IBM Data Studio pureQuery Runtime 1.2
· IBM Data Studio pureQuery Runtime for z/OS 1.2
· IBM Data Studio Administrator for DB2 for Linux, UNIX, and Windows 1.2
The value these new releases deliver includes:
· Improve Java data access performance for DB2 – without changing a line of code
· Speed up problem isolation for developers – even when using Java frameworks like Hibernate, OpenJPA, Spring, and others
· Build out the family integration in the administration space with Data Studio Administrator
Let me go through each of these in a little detail:
Improve Java data access performance for DB2 – without changing a line of code
IBM Data Studio Developer 1.2 together with IBM Data Studio pureQuery Runtime 1.2 now provide client optimization. This release provides client optimization for JDBC access that lets you turn dynamic JDBC execution into static execution without changing a single line of source code - in fact, you don’t even have to have the source code. We capture the SQL from the application and provide tooling in Data Studio Developer to help the developer or DBA view, edit, bind, verify, and version the packages to enable static execution.
As you may know, I’m a big proponent of static SQL because it can improve throughput, make response times more stable, improve security, provide more information for capacity planning, and drive down CPU cycles. You can read more about static SQL benefits here.
I’m also very happy to have pureQuery runtime capability on z/OS for both DB2 V8 and V9. You can now develop pureQuery applications, Web services, and stored procedures for native z/OS deployment, and use client optimization for JDBC access for existing z/OS Java applications. This can add up to huge savings for z/OS environments. Make sure you see this article that includes details of our testing to quantify the performance benefits and CPU savings that pureQuery can bring to DB2 for z/OS.
Speed up problem isolation for developers – even when using Java frameworks like Hibernate, OpenJPA, Spring, and others
How much time do you (whether a developer or DBA) spend trying to isolate performance issues first to a specific SQL statement, then to the source application, then to the originating code? It gets more complex with the three-tier architectures and when popular frameworks are used. Developers may never even see the SQL generated by the framework. Data Studio Developer 1.2 makes it easier to isolate problematic SQL. First, it is much easier to associate SQL with static packages rather than a generic package name used with dynamic JDBC. And second, Data Studio Developer provides an outline view that traces SQL statements back to the originating line in the source application (whether you’re executing it statically or not). In addition, it shows SQL and table relationships so impact analysis is easier since we can get answer to questions like “Where is this column used in my application” or “What tables does this application access” or “What SQL does that application issues against this table?”.
Build out the family integration in the administration space with Data Studio Administrator
OK, time for me to go. See the announcement letters for both the z/OS and Linux, Unix, Windows releases for more information about these new releases and when they are expected to be available. And keep an eye on this blog and the Data Studio community space for more details and to join in with other users.
Talk to you soon.
-- Curt Cotner