Application areas
Posts focusing on the use of database and analytic technologies in specific application domains. Related subjects include:
- Any subcategory
- (in Text Technologies) Specific application areas for text analytics
Columnar DBMS vendor customer metrics
Last April, I asked some columnar DBMS vendors to share customer metrics. They answered, but it took until now to iron out a couple of details. Overall, the answers are pretty impressive. Read more
Infobright 4.0
Infobright is announcing its 4.0 release, with imminent availability. In marketing and product alike, Infobright is betting the farm on machine-generated data. This hasn’t been Infobright’s strategy from the getgo, but it is these days, with pretty good focus and commitment. While some fraction of Infobright’s customer base is in the Sybase-IQ-like data mart market — and indeed Infobright put out a customer-win press release in that market a few days ago — Infobright’s current customer targets seem to be mainly:
- Web companies, many of which are already MySQL users.
- Telecommunication and similar log data, especially in OEM relationships.
- Trading/financial services, especially at mid-tier companies.
Key aspects of Infobright 4.0 include: Read more
| Categories: Data warehousing, Database compression, Infobright, Investment research and trading, Log analysis, Open source, Telecommunications, Web analytics | 8 Comments |
Dirty data, stored dirt cheap
A major driver of Hadoop adoption is the “big bit bucket” use case. Users take a whole lot of data, often machine-generated data in logs of different kinds, and dump it into one place, managed by Hadoop, at open-source pricing. Hadoop hardware doesn’t need to be that costly either. And once you get that data into Hadoop, there are a whole lot of things you can do with it.
Of course, there are various outfits who’d like to sell you not-so-cheap bit buckets. Contending technologies include Hadoop appliances (which I don’t believe in), Splunk (which in many use cases I do), and MarkLogic (ditto, but often the cases are different from Splunk’s). Cloudera and IBM, among other vendors, would also like to sell you some proprietary software to go with your standard Apache Hadoop code.
So the question arises — why would you want to spend serious money to look after your low-value data? The answer, of course, is that maybe your log data isn’t so low-value. Read more
| Categories: Hadoop, Investment research and trading, Log analysis, Splunk | 9 Comments |
The essence of an application
Once upon a time, information technology was strictly about — well, information. And by “information” what was meant was “data”.* An application boiled down to a database design, plus a straightforward user interface, in whatever the best UI technology of the day happened to be. Things rarely worked quite as smoothly as the design-database/press-button/generate-UI propaganda would have one believe, but database design was clearly at the center of application invention.
*Not coincidentally, two of the oldest names for “IT” were data processing and management information systems.
Eventually, there came to be three views of the essence of IT:
- Data — i.e., the traditional view, still exemplified by IBM and Oracle.
- People empowerment — i.e., Microsoft-style emphasis on UI friendliness and efficiency.
- Operational workflow — i.e., SAP-style emphasis on actual business processes.
Graphical user interfaces were a major enabling technology for that evolution. Equally important, relational databases made some difficult problems easy(ier), freeing application designers to pursue more advanced functionality.
Based on further technical evolution, specifically in analytic and consumer technologies, I think we should now take that list up to five. The new members I propose are:
- Investigative analytics.
- Emotional response.
| Categories: Data warehousing, Facebook, Predictive modeling and advanced analytics, Theory and architecture, Web analytics | 1 Comment |
Application areas for SAS HPA
When I talked with SAS about its forthcoming in-memory parallel SAS HPA offering, we talked briefly about application areas. The three SAS cited were:
- Consumer financial services. The idea here is to combine information about customers’ use of all kinds of services — banking, credit cards, loans, etc. SAS believes this is both for marketing and risk analysis purposes.
- Insurance. We didn’t go into detail.
- Mobile communications. SAS’ customers aren’t giving it details, but they’re excited about geocoding/geospatial data.
Meanwhile, in another interview I heard about, SAS emphasized retailers. Indeed, that’s what spawned my recent post about logistic regression.
The mobile communications one is a bit scary. Your cell phone — and hence your cellular company — know where you are, pretty much from moment to moment. Even without advanced analytic technology applied to it, that’s a pretty direct privacy threat. Throw in some analytics, and your cell company might know, for example, who you hang out with (in person), where you shop, and how those things predict your future behavior. And so the government — or just your employer — might know those things too.
| Categories: Application areas, Predictive modeling and advanced analytics, SAS Institute, Surveillance and privacy, Telecommunications | 2 Comments |
Notes on short-request scale-out MySQL
A press person recently asked about:
… start-ups that are building technologies to enable MySQL and other SQL databases to get over some of the problems they have in scaling past a certain size. … I’d like to get a sense as to whether or not the problems are as severe and wide spread as these companies are telling me? If so, why wouldn’t a customer just move to a new database?
While that sounds as if he was asking about scale-out relational DBMS in general, MySQL or otherwise, short-request or analytic, it turned out that he was asking just about short-request scale-out MySQL. My thoughts and comments on that narrower subject include(d) but are not limited to: Read more
Revolution Analytics update
I wasn’t too impressed when I spoke with Revolution Analytics at the time of its relaunch last year. But a conversation Thursday evening was much clearer. And I even learned some cool stuff about general predictive modeling trends (see the bottom of this post).
Revolution Analytics business and business model highlights include:
- Revolution Analytics is an open-core vendor built around the R language. That is, Revolution Analytics offers proprietary code and support, with subscription pricing, that help in the use of open source software.
- Unlike most open-core vendors I can think of, Revolution Analytics takes little responsibility for the actual open source part. Some “grants” for developing certain open source R pieces seem to be the main exception. While this has caused some hard feelings, I don’t have an accurate sense for their scope or severity.
- Revolution Analytics also sells a single-user/workstation version of its product, freely admitting that this is mainly a lead generation strategy or, in my lingo, a “break-even leader.”
- Revolution Analytics boasts around 100 customers, split about 70-30 between the workstation seeding stuff and the real server product.
- Revolution Analytics has “about” 37 employees. Headquarters are at 101 University Avenue (do I have to say in what city? 🙂 ). There are also a development office in Seattle and a sales office in New York.
- Revolution Analytics’ pricing is by size of server. “Small” servers — i.e. up to 12 cores — start at $25K/year.
- Unsurprisingly, adoption is more alongside SAS et al. than rip-and-replace.
| Categories: Health care, Investment research and trading, Open source, Parallelization, Predictive modeling and advanced analytics, Pricing, Revolution Analytics, SAS Institute | 2 Comments |
Some quick notes on HP-Vertica
HP is acquiring Vertica. Read more
| Categories: In-memory DBMS, Investment research and trading, Memory-centric data management, StreamBase, Streaming and complex event processing (CEP), VoltDB and H-Store | 13 Comments |
Membase and CouchOne merged to form Couchbase
Membase, the company whose product is Membase and whose former company name is Northscale, has merged with CouchOne, the company whose product is CouchDB and whose former name is Couch.io. The result (product and company) will be called Couchbase. CouchDB inventor Damien Katz will join the Membase (now Couchbase) management team as CTO. Couchbase can reasonably be regarded as a document-oriented NoSQL DBMS, a product category I not coincidentally posted about yesterday.
In essence, Couchbase will be CouchDB with scale-out. Alternatively, Couchbase will be Membase with a richer programming interface. The Couchbase sweet spot is likely to be: Read more
| Categories: Application areas, Cache, Couchbase, CouchDB, Market share and customer counts, memcached, NoSQL, Open source, Parallelization, Solid-state memory | 2 Comments |
Cassandra company DataStax (formerly Riptano) is on track
Riptano, the Cassandra company, has changed its name to DataStax. DataStax has opened headquarters in Burlingame and hired some database-experienced folks – notably Ben Werther from Greenplum and Michael Weir from ParAccel, with Zenobia Godschalk (who worked with Aster Data) somewhere in the outside PR mix. Other than that, what’s new at DataStax is pretty much what could have been expected based on what DataStax folks said last spring.
Most notably, DataStax is introducing a software offering, whose full name is DataStax OpsCenter for Apache Cassandra. DataStax OpsCenter for Apache Cassandra seems to be, in essence, a monitoring tool for Cassandra clusters, with a bit of capacity planning bundled in. (If there are any outright operations parts to DataStax OpsCenter, they got overlooked in our conversation.)* Read more