Coral8 versus StreamBase
Besides talking about what Coral8 and StreamBase (and other CEP vendors) have in common, Mark Tsimelzon and I talked quite a bit about what he sees as some of the important differences. There were a lot, of course, but three in particular stood out.
1. Mark believes Coral8 has significantly lower latency than StreamBase. E.g., the Wombat/Coral8 combo achieves sub-millisecond latency, with Coral8 itself consuming less than a tenth of that. The best comparable figures from StreamBase that I currently know of are almost an order of magnitude slower.
Top-end speed aside, Mark believes that Coral8 is fundamentally better suited for complex queries and pattern recognition, while StreamBase works well with simpler queries. For example, his other performance claims notwithstanding, he concedes that StreamBase is at least comparable to Coral8 in its throughput for huge numbers of simple queries. (The number he mentioned was ½ million queries/second.) Indeed, while we barely talked about customer/marketing issues, Mark asserts that the companies’ respective customer bases reflect this complex/simple distinction.*
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| Categories: Aleri and Coral8, Memory-centric data management, Progress, Apama, and DataDirect, StreamBase, Streaming and complex event processing (CEP) | 5 Comments |
The essence of CEP according to Coral8
Last week, I complained that my first briefing with Coral8 wasn’t very technical. Wednesday I had a call with Mark Tsimelzon, CTO and founder of Coral8, and he made up for that in spades. In this post I’ll cover some of his general comments. Others will touch on more Coral8-specific topics, and his view of the Coral8/StreamBase comparison.
As Mark describes it, the big difference between a DBMS – even an in-memory DBMS – and a complex event processing engine is this: CEP engines do instantaneous incremental processing. He commonly refers to this as registering queries and operators for incremental evaluation. For example, suppose you need to maintain the sum of some data stream over the past 10 minutes. Then each second (or other short unit of time), the system adds in all the values that arrived in the past second, and subtracts all those that arrived 600-601 seconds ago. Voila! The sum is incrementally updated.
Now, rolling sums may not sound very interesting – but where you have rolling sums, you trivially also have rolling averages (just divide the sum by the count) and rolling standard deviations (same idea, with some squares and square roots mixed in). Those, of course, are primitives in Coral8 too. Ditto rolling maxima and minima. Ditto rolling joins (which are updated a lot like materialized views).
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| Categories: Aleri and Coral8, Memory-centric data management, Streaming and complex event processing (CEP) | 2 Comments |
Competitive claims in CEP
For the most part, the vendors I talk with in complex event/stream processing like and speak well of each other (most of the exceptions seem to involve StreamBase). Even so, there are a lot of interesting competitive claims and counterclaims in this market. Prior posts and comment threads have covered Apama/StreamBase jousting on the subjects of who has more business and how many financial data feeds StreamBase supports. Other areas that generate interesting sparks are performance, parallelism, and determinism. Read more
| Categories: Aleri and Coral8, Investment research and trading, Memory-centric data management, Progress, Apama, and DataDirect, StreamBase, Streaming and complex event processing (CEP) | 1 Comment |
A deeper dive into Apama
My recent non-technical Apama briefing has now had a much more technical sequel, with charming founder and former Cambridge professor John Bates. He still didn’t fully open the kimono – trade secrets and all that — but here’s the essence of what’s going on.
Complex event/stream processing (CEP) is all about looking for many patterns at once. Reality – the stream(s) of data – is checked against these patterns for matches. In Apama, these patterns are kept in a kind of tree – they call it a hypertree — and John says the work to check them is only logarithmic in the number of patterns.
Since patterns commonly have multiple parts — and usually also take time to unfold — what really goes on is that partial matches are found, after which what’s being matched against is the REMAINDER of the pattern. Thus, there’s constant pruning and rebalancing of the tree. What’s more, a large fraction of all patterns – at least in the financial trading market — involve a short time window, which again creates a need for ongoing, rapid tree modification. Read more
| Categories: Memory-centric data management, Progress, Apama, and DataDirect, Streaming and complex event processing (CEP) | 4 Comments |
The Coral8 story
Complex event/stream processing vendor Coral8 raised its hand and offered a briefing – non-technical, alas, but at least it was a start. Here are some of the highlights: Read more
An era of easier database portability?
More and more, I find myself addressing questions of database portability and transparency, most particularly in the cases of EnterpriseDB, Ants Software, and now also Dataupia. None of those three efforts is very large yet, but so far I’d rate their respective buzzes to be very encouraging in the case of EnterpriseDB, non-discouraging or better in the case of Ants, and too early to judge for Dataupia. On the whole, it definitely seems like a matter worthy of attention.
With that as backdrop, where is all this compatibility/portability/transparency stuff going to lead? Read more
| Categories: ANTs Software, Dataupia, Emulation, transparency, portability, EnterpriseDB and Postgres Plus, Progress, Apama, and DataDirect | 2 Comments |
Filemaker for composite application development
It’s not accurate to judge a product by its most obnoxious or least clueful partisans. Hence, even though some insult-spewers take umbrage at an accurate description of FileMaker’s capabilities,* it wouldn’t be fair to write the product off entirely.
*Mercifully, none of said insult-spewers seems to actually work at the company. I must confess that this makes it easier for me to take the (somewhat) high road here.
Possibly due to an actual understanding of enterprise technology, Tim Dietrich has weighed in on on the discussion from a different angle. Here’s a quote in which he gives an example of very successful FileMaker use:
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| Categories: EAI, EII, ETL, ELT, ETLT, FileMaker | 2 Comments |
Dataupia – low-end data warehouse appliances
It’s unfortunate that Dataupia has concepts like “Utopia” and “Satori” in its marketing, as those serve to obscure what the company really offers – data warehouse appliances designed for the market’s low end. Indeed, it seems that they’re currently very low-end, because they were just rolled out in May and are correspondingly immature.
Basic aspects include:
- Type 1 appliances, which most other data warehouse appliance vendors (Teradata excepted) have moved away from. And there actually seems to be very little special about the hardware design to take advantage of the proprietary opportunity.
- Apparently limited redistribution of intermediate query result sets – i.e, the “fat head” architecture most competitors have moved away from. But it’s not pure fat-head; there’s some data redistribution.
- General lack of partnerships with the obvious software players (but they’re working on that).
- Low price point ($19,500 per 2-terabyte module).
Beyond price, Dataupia’s one big positive differentiation vs. alternative products is that you don’t write SQL directly to a Dataupia appliance. Rather, you talk to it through the federation capability in your big-brand DBMS, such as Oracle or SQL*Server. Benefits of this approach include: Read more
| Categories: Data warehouse appliances, Data warehousing, Dataupia, Emulation, transparency, portability | 3 Comments |
DATAllegro heads for the high end
DATAllegro Stuart Frost called in for a prebriefing/feedback/consulting session. (I love advising my DBMS vendor clients on how to beat each other’s brains in. This was even more fun in the 1990s, when combat was generally more aggressive. Those were also the days when somebody would change jobs to an arch-rival and immediately explain how everything they’d told me before was utterly false …)
While I had Stuart on the phone, I did manage to extract some stuff I’m at liberty to use immediately. Here are the highlights: Read more
| Categories: Data warehouse appliances, Data warehousing, Database compression, DATAllegro, Greenplum, Netezza, Teradata | 4 Comments |
EnterpriseDB has a huge partisan in FTD
The Register has a rip-roaring story on a (currently partial) conversion from Oracle to EnterpriseDB. Basically, FTD is royally pissed-off at Oracle, and EnterpriseDB stepped in with a very fast conversion.
Apparently, FTD decided they needed to Do Something after a Valentine’s Day meltdown, and the project was completed on EnterpriseDB in time for Mother’s Day.
One note of caution: When a user supports a vendor’s marketing this emphatically, it usually has gotten nice breaks on price and/or service. Your mileage may vary. On the other hand, EnterpriseDB is still a small enough company that, if you want them to love you to death, you can be pretty well assured that you’re important enough to them that they’ll do so.
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