StreamBase
Analysis of complex event/stream processing vendor StreamBase. Related subjects include:
More on stream processing integration with disk-based DBMS
Mike Stonebraker wrote in with one “nit pick” about yesterday’s blog. I had credited Truviso for strong DBMS/stream processor integration. He shot back that StreamBase has Sleepycat integrated in-process. He further pointed out that a Sleepycat record lookup takes only 5 microseconds if the data is in cache. Assuming what he means is that it’s in Sleepycat’s cache, that would be tight integration indeed.
I wonder whether StreamBase will indefinitely rely on Sleepycat, which is of course now an Oracle product …
| Categories: Memory-centric data management, Michael Stonebraker, Oracle, StreamBase, Streaming and complex event processing (CEP) | Leave a Comment |
Mike Stonebraker on financial stream processing
After my call with Truviso and blog post referencing same, I had the chance to discuss stream processing with Mike Stonebraker, who among his many other distinctions is also StreamBase’s Founder/CTO. We focused almost exclusively on the financial trading market. Here are some of the highlights. Read more
| Categories: Memory-centric data management, Michael Stonebraker, StreamBase, Streaming and complex event processing (CEP), Truviso | Leave a Comment |
StreamBase and Truviso
StreamBase is a decently-established startup, possibly the largest company in its area. Truviso, in the process of changing its name from Amalgamated Insight, has a dozen employees, one referenceable customer, and a product not yet in general availability. Both have ambitious plans for conquering the world, based on similar stories. And the stories make a considerable amount of sense.
Both companies’ core product is a memory-centric SQL engine designed to execute queries without ever writing data to disk. Of course, they both have persistence stories too — Truviso by being tightly integrated into open-source PostgreSQL, StreamBase more via “yeah, we can hand the data off to a conventional DBMS.” But the basic idea is to route data through a whole lot of different in-memory filters, to see what queries it satisfies, rather than executing many queries in sequence against disk-based data. Read more
| Categories: Memory-centric data management, PostgreSQL, StreamBase, Streaming and complex event processing (CEP), Truviso | 8 Comments |
Oracle, Tangosol, objects, caching, and disruption
Oracle made a slick move in picking up Tangosol, a leader in object/data caching for all sorts of major OLTP apps. They do financial trading, telecom operations, big web sites (Fedex, Geico), and other good stuff. This is a reminder that the list of important memory-centric data handling technologies is getting fairly long, including:
- Object caching (e.g., Tangosol, Progress ObjectStore)
- In-memory RDBMS (e.g., Oracle TimesTen, Solid BoostEngine, McObject eXtremeDB)
- Stream processing (e.g., Progress Apama, Streambase)
And that’s just for OLTP; there’s a whole other set of memory-centric technologies for analytics as well.
When one connects the dots, I think three major points jump out:
- There’s a lot more to high-end OLTP than relational database management.
- Oracle is determined to be the leader in as many of those areas as possible.
- This all fits the market disruption narrative.
I write about Point #1 all the time. So this time around let me expand a little more on #2 and #3.
Read more
Mike Stonebraker Blasts “One Size Fits All”
When it comes to DBMS inventors, Mike Stonebraker is the next closest thing to Codd. And he’s become a huge non-believer in the idea that one DBMS architecture meets all needs.
Frankly, there isn’t much in that paper that hasn’t already been said in this blog, except for the part that is specifically relevant to one of his startups, StreamBase. Still, it’s nice to have the high-powered agreement.
More recently, the argument in that paper has been extended with a benchmark-filled follow-up based on another Stonebraker startup, Vertica.