Sneakernet to the cloud

Recently, Amazon CTO Werner Vogels put up a blog post which suggested that, now and in the future, the best way to get large databases into the cloud is via sneakernet.  In some circumstances, he is surely right. Possible implications include:

• When sending data to the cloud, you probably want to compress it to the max before sending. Clearpace’s new RainStor structured-data archiving service emphasizes that idea. RainStor marketing says cloud, cloud, cloud — but Clearpace thinks you really should have a bit of its software onsite too, to compress the data before sending it across the wire.
• Getting data from one cloud to another cloud could be problematic. I’m fond of saying that weblog data naturally lives in the cloud at your hosting company’s location, so you should analyze it there too. But this makes the most sense if you analyze it or at least filter/reduce it in place.  (That said, the really, really big web companies have lots of different data centers, and presumably do move huge amounts of log data from place to place.)

But for one-time moves of data sets — sure, sneaker net/snail mail should work just fine.

Amazon Elastic MapReduce

Amazon is introducing a beta of Amazon Elastic MapReduce.  What it boils down to is cheap, on-demand Hadoop.

This seems like a great way to experiment with MapReduce and see if you like it. But for serious use, I don’t know why you wouldn’t prefer MapReduce more closely integrated into a DBMS.

April Fool’s Day highlights

Amazon says it’s taking “cloud” computing to new heights, as it were.

Derivative funds and large government-subsidized entities will be especially interested in FACE’s transmodal operation. They can allocate a dedicated FACE, load it up with data, and then send it out to sea to perform advanced processing in safety. The government will have absolutely no chance of acting against them, because they will be too busy trying to decide which Federal Air Regulation (FAR) was violated, not to mention scheduling news conferences.

First excellent April Fool’s joke I saw this year was from The Guardian.  The best so far is from Expedia.  Others are linked in my Twitter feed.  And personally, I’m encouraging the concept of April No-Fooling Day.

SAS in its own cloud

The Register has a fairly detailed article about SAS expanding its cloud/SaaS offerings.  I disagree with one part, namely:

SAS may not have a choice but to build its own cloud. Given the sensitive nature of the data its customers analyze, moving that data out to a public cloud such as the Amazon EC2 and S3 combo is just not going to happen.

And even if rugged security could make customers comfortable with that idea, moving large data sets into clouds (as Sun Microsystems discovered with the Sun Grid) is problematic. Even if you can parallelize the uploads of large data sets, it takes time.

But if you run the applications locally in the SAS cloud, then doing further analysis on that data is no big deal. It’s all on the same SAN anyway, locked down locally just as you would do in your own data center.

I fail to see why SAS’s campus would be better than leading hosting companies’ data centers for either of data privacy/security or data upload speed.  Rather, I think major reasons for SAS building its own data center for cloud computing probably focus on: Read more

IBM in the cloud

IBM is making DB2, Informix Dynamic Server, and other products available in the Amazon cloud.  The press release says test and development are free, while production will be charged at an hourly rate.  No doubt more price details will be forthcoming when the whole thing is fully in production.

Frankly, I’ve lost track of who all has some kind of cloud or SaaS offering now.  The list is at least Oracle, IBM, presumably Microsoft, MySQL (via Elastra, and also at almost every web host), PostgreSQL (ditto, more or less), EnterpriseDB, Kognitio, Vertica, Netezza, Aster Data.  No doubt I’m forgetting a bunch more.

Aster Data in the cloud

Aster Data is in the news, bragging about a cloud version of nCluster, and providing both a press release and a blog post on the subject. It seems there are three actual customers, two of which have been publicly named. One of them, ShareThis, is in production. (2 terabytes of data on 9 nodes, planning to scale to 10-18 TB on 24 or so nodes by year-end.) All seem to be doing something in the area of internet marketing, web analytics or otherwise — which makes sense, as the same could be said of almost all Aster customers overall. That said, it seems that these customers are doing their primary analytic processing remotely, which makes Aster’s experience in that regard more akin to Kognitio’s than to Vertica’s. Read more

Database SaaS gains a little visibility

Way back in the 1970s, a huge fraction of analytic database management was done via timesharing, specifically in connection with the RAMIS and FOCUS business-intelligence-precursor fourth-generation languages.  (Both were written by Gerry Cohen, who built his company Information Builders around the latter one.)  The market for remoting-computing business intelligence has never wholly gone away since. Indeed, it’s being revived now, via everything from the analytics part of Salesforce.com to the service category I call data mart outsourcing.

Less successful to date are efforts in the area of pure database software-as-a-service.  It seems that if somebody is going for SaaS anyway, they usually want a more complete, integrated offering. The most noteworthy exceptions I can think of to this general rule are Kognitio and Vertica, and they only have a handful of database SaaS customers each. To wit: Read more

Multitenancy hype is getting out of control

I posted recently on SaaS-data-integration-in-the-cloud, and a couple of vendors stopped by the comment thread to shared what they do. One was Boomi, which has a blog that does a good job of spelling out its opinions. What the Boomi blog is not so good at, however, is giving any good reasons why one should share those opinions.

I refer specifically to a couple of posts claiming that multitenancy is somehow crucial for SaaS data integration to work. To this I can only say — huh? A decent data integration system should be able to handle many parallel threads at once, connecting many pairs of databases at once. So the hard part of multitenancy is pretty much “free.” If, even so, the integration provider chooses not to go fully multitenant, whose business is it but theirs? Read more

Everybody’s putting integration services in the cloud

Both Pervasive Software and Cast Iron Systems told me recently of fairly pure cloud offerings. In this, they’re joining Informatica, which started offering Salesforce.com integration-as-a-service back in 2006. So far as I can tell, the three vendors are doing somewhat different things. Read more

The essence of the Oracle Amazon cloud offering

OK. The press release adds color to what I previously posted about Oracle’s new Amazon cloud offering. Read more

Oracle announces an Amazon cloud offering

Per the Amazon Web Service Blog, Oracle announced that Oracle can be run in the Amazon cloud (i.e., on EC2, with EBS for persistent storage). Clustering is probably weak, however — e.g., there’s no RAC support, as per Oracle’s well-written FAQ. Perhaps not coincidentally, the FAQ seems to suggest that the primary use case at this time is for backup, and backup is generally a major point of emphasis on Oracle’s cloud computing page.

Of course, another use case could be development, but that depends in part on pricing. Of course, whether Oracle’s offering seems attractively priced compared with, for example, a similar one from EnterpriseDB and Elastra depends a lot on whether you’ve already negotiated an unlimited-use license for Oracle.

James Kobielus, who presumably was pre-briefed, has more to say.

Some Elastra numbers

GigaOm reports that Elastra just raised $12 million, and that it has 40 paying customers, up from 13 around the time of Elastra’s March launch.

Project Cassandra — Facebook’s open sourced quasi-DBMS

Facebook has open-sourced Project Cassandra, an imitation of Google’s BigTable.  Actual public information about Facebook’s Cassandra seems to reside in a few links that may be found on the Cassandra Project’s Google code page.  All the discussion I’ve seen seems to be based solely on some slides from a SIGMOD presentation. In particular, Dare Obasanjo offers an excellent overview of Cassandra.  To wit: Read more

Jerry Held on cloud data warehousing and how business intelligence will be transformed by it

Vertica Chairman Jerry Held has a pair of blog posts on analytics and data warehousing in the cloud. The first lays out a number of potential benefits and consequences of cloud data warehousing, under the heading of “Transforming BI”: Read more

Vertica in the cloud

I may have gotten confused again as to an embargo date, but if so, then this time I had it late rather than early. Anyhow, the TDWI-timed news is that Vertica is now available in the Amazon cloud. Of course, the new Vertica cloud offering is:

• Super-easy to set up
• Pay-as-you-go.

Slightly less obviously:

• Vertica insists its software was designed for grid computing from the ground up, and hence doesn’t need Elastra’s administrative aids for starting, stopping, and/or provisioning instances.
• This is a natural fit for new or existing Vertica customers in data mart outsourcing.

Other coverage:

• IDG
• Tom Briggs
• Philip Howard

Related link

• Vertica Chairman Jerry Held’s views on cloud data warehousing, and my reaction to same

Outsourced data marts

Call me slow on the uptake if you like, but it’s finally dawned on me that outsourced data marts are a nontrivial segment of the analytics business. For example:

• I was just briefed by Vertica, and got the impression that data mart outsourcers may be Vertica’s #3 vertical market, after financial services and telecom. Certainly it seems like they are Vertica’s #3 market if you bundle together data mart outsourcers and more conventional OEMs.
• When Netezza started out, a bunch of its early customers were credit data-based analytics outsourcers like Acxiom.
• After nagging DATAllegro for a production reference, I finally got a good one — TEOCO. TEOCO specializes in figuring out whether inter-carrier telcom bills are correct. While there’s certainly a transactional invoice-processing aspect to this, the business seems to hinge mainly around doing calculations to figure out correct charges.
• I was talking with Pervasive about Pervasive Datarush, a beta product that lets you do super-fast analytics on data even if you never load it into a DBMS in the first place. I challenged them for use cases. One user turns out to be an insurance claims rule-checking outsourcer.
• One of Infobright’s references is a French CRM analytics outsourcer, 1024 Degres.
• 1010data has built up a client base of 50-60, including a number of financial and retail blue-chippers, with a soup-to-nuts BI/analysis/columnar database stack.
• I haven’t heard much about Verix in a while, but their niche was combining internal sales figures with external point-of-sale/prescription data to assess retail (especially pharma) microtrends.

To a first approximation, here’s what I think is going on. Read more

Pervasive is also pursuing simplicity and SaaS integration

I blogged recently about Cast Iron Systems, a simplicity-oriented data integration appliance vendor that is increasingly focusing on the SaaS market. Well, Pervasive Software is doing something similar.

Via Data Integrator, Pervasive is a leader in the low-cost integration market, with revenue split about 50/25/25 between direct sales, ISVs, and SaaS. Pervasive fondly believes that its products cost half as much as Cast Iron’s, and wind up taking no more installation effort when you factor in Pervasive’s broader capabilities in areas such as workflow. However, there’s some doubt as to whether this is apples-to-apples. Cast Iron does include hardware, after all, and as Pervasive itself points out, Cast Iron will bundle some professional services into a sale if you ask nicely.

Two things are new. Read more

Elastra launched today

At Elastra’s request, I didn’t write further about them back when I was interested in doing so. But you can go find out about them yourself. Basically, their secret sauce is that they write deployment instructions in a few hundred lines of two proprietary markup languages. They have ambitions beyond DBMS, and beyond the Amazon cloud.

According to their slides, they have 13 paying customers.

Cast Iron Systems focuses on SaaS data integration

When I wrote about data integration vendor Cast Iron Systems a year ago, its core message was “simplicity, simplicity, simplicity.” Supporting points included:

1. An appliance delivery format.
2. Lots of heuristics for automatic mapping and quick set-up. E.g., Cast Iron claims that 70% of a typical SAP-Salesforce.com connection can be done straight out of the box.
3. The absence of data cleaning/transformation features that might complicate things.

Cast Iron still believes in all that.

Even so, its messaging has changed a bit. Cast Iron now bills itself, in the first sentence of its press release boilerplate, as “the fastest growing SaaS integration appliance vendor.” And when I talked with marketing chief Simon Peel today, the only use cases we discussed were connections between SaaS and on-premises apps. Read more

Microsoft SQL Server Data Services

As usual, Microsoft forgot to brief me, but Mary Jo Foley reports on Microsoft SQL Server Data Services. A look at the official site clarifies that this database-in-a-cloud offering uses “Microsoft SQL Server as a data storage node.” However, there seems to be a software layer on top of SQL Server providing scale-out and appropriate management.

In addition to the more-than-SQL-Server layer, there seems to be a less-than-SQL-Server aspect as well. In a particular, Microsoft SQL Server Data Services boasts “Support for simple types: string, numeric, datetime, boolean.” XML is the “primary wire format,” and hints dropped about the schema philosophy sound XMLish too.

Interestingly, Foley reports that Microsoft plans to offer an on-premises version of Microsoft SQL Server Data Services as well.

EnterpriseDB on Elastra, early stages

I finally caught up with Bob Zurek about EnterpriseDB’s foray into the Elastra cloud. Here are some highlights:

• There have been dozens of applicants for the EnterpriseDB/Elastra beta program. As is usual in limited beta programs, EnterpriseDB is trying to sort out the ones who’ll make a big commitment from the tire-kickers.
• The main interest in EnterpriseDB/Elastra has come from ISVs, and secondarily from purely online businesses (e.g., SaaS vendors, web businesses, and a large MMO game vendor). There’s been a little interest from enterprises.
• Significant fractions of the EnterpriseDB/Elastra beta applications come from each of the Oracle, PostgreSQL, and MySQL user communities. A few come from SQL Server. None come from DB2.
• Bob praised Elastra for its technology in clustering, starting/stopping instances, etc. He also said that EnterpriseDB had “educated” Elastra on EnterpriseDB internals and/or admin tools, to make the integration work.
• EnterpriseDB will start turning on a few beta Elastra customers any day now (i.e., it may well not take until March, the original target).

Why not database SaaS?

After a flurry of recent announcements of database SaaS (Software as a Service), eWeek has published a backlash article. The angle is that database SaaS is too expensive, because you can get decent DBMS for free and per-gig usage charges might be expensive for big databases.

I think that’s missing the point. Most OLTP databases are pretty small. Or, if they’re big, they get that way through a lot of transactions. In the first case, hosted management is cheap. In the second case, hosted management is taking care of a large burden for you. Read more

EnterpriseDB joins Elastra in the Amazon cloud

When Elastra announced their service to host MySQL and PostgreSQL in the Amazon S3/EC2 cloud, I immediately told my dear darling clients at EnterpriseDB they should do the same. Whereupon they told me it would happen soon. However, they neglected to tell me when it was actually announced. So I know no more than can be found in this Computerworld article.

But I’ll say this — it’s a very tempting option, both for new web-based applications or businesses, or simply as a development platform pending later redeployment.

The Great MapReduce Debate

Google’s highly parallel file manipulator MapReduce has gotten great attention recently, after a research paper revealed:

• MapReduce is running the core Google search engine, plus much of Google Analytics and other applications.
• MapReduce is processing 400+ petabytes of data per month.

(Niall Kennedy popularized the paper and surveyed its results.)

David DeWitt and Mike Stonebraker then launched a blistering attack on MapReduce, accusing it of disregarding almost all the lessons of database management system theory and practice. A vigorous comment thread has ensued, pointing out that MapReduce is not a DBMS and asserting it therefore shouldn’t be judged as one.

While correct, that defense begs the question – what is MapReduce good for? Proponents of MapReduce highlight two advantages:

1. MapReduce makes it very easy to program data transformations, including ones to which relational structures are of little relevance.
2. MapReduce runs in massively parallel mode “for free,” without extra programming.

Based on those advantages, MapReduce would indeed seem to have significant uses, including: Read more

LongJump is probably doing something interesting

According to VentureBeat, LongJump is offering a SaaS version of a “relational database architecture.” It’s also a “simple XML server.” And there are apps and workflow management. According to LongJump itself, there is “full search” and “wide palette of field types” and “multi-app mashup.” And since it’s a SaaS offering, the LongJump website also spends a whole page telling us how wonderful RackSpace is.

If VentureBeat got the “relational” part of the story wrong — perhaps out of confusion with Longjump’s parent company’s name “Relationals” — then the rest of it kind of hangs together: XML, composite apps, and so on. Otherwise — well, relational access, XML, and search can certainly be combined in a single package, as per MarkLogic, Attivio, or for that matter Oracle, DB2, and Microsoft SQL Server. But all that and apps and app dev too seem a lot to bite off for a single self-funded startup.

Next Page →

Subscribe to the Monash Research feed via RSS or email:

Login

Search our blogs and white papers

Monash Research blogs

• DBMS2 covers database management, analytics, and related technologies.
• Text Technologies covers text mining, search, and social software.
• Strategic Messaging analyzes marketing and messaging strategy.
• The Monash Report examines technology and public policy issues.
• Software Memories recounts the history of the software industry.

User consulting

Building a short list? Refining your strategic plan? We can help.

Vendor advisory

We tell vendors what's happening -- and, more important, what they should do about it.

Monash Research highlights

Learn about white papers, webcasts, and blog highlights, by RSS or email.

• Recent posts

  • User data vs. raw disk space as a marketing metric
  • The TPC-H schema
  • Notes on columnar/TPC-H compression
  • Storage humor
  • NoSQL?

• Categories

  • About this blog
  • Analytic technologies
    • Business intelligence
    • Data mart outsourcing
    • Data warehousing
    • MOLAP
  • Application areas
    • Games and virtual worlds
    • Investment research and trading
    • Scientific research
    • Telecommunications
    • Web analytics
  • Buying processes
    • Benchmarks and POCs
  • Companies and products
    • 1010data
    • Ab Initio Software
    • Aleri and Coral8
    • Alpha Five
    • Amazon and its cloud
    • ANTs Software
    • Aster Data
    • Business Objects
    • Calpont
    • Cast Iron Systems
    • Clearpace
    • Cloudera
    • Cogito and 7 Degrees
    • Cognos
    • CouchDB
    • DATAllegro
    • Dataupia
    • Elastra
    • EMC
    • EnterpriseDB and Postgres Plus
    • Exasol
    • Expressor
    • FileMaker
    • Google
    • Greenplum
    • Hadoop
    • HP and Neoview
    • IBM and DB2
      • pureXML
    • illuminate Solutions
    • Infobright
    • Informatica
    • Information Builders
    • Inforsense
    • Ingres
    • Intel
    • Intersystems and Cache'
    • Jaspersoft
    • Kalido
    • Kickfire
    • Kognitio
    • Mark Logic
    • McObject
    • Microsoft and SQL*Server
    • MySQL
    • Netezza
    • Oracle
      • Exadata
    • Oracle TimesTen
    • ParAccel
    • Pentaho
    • Pervasive Software
    • PostgreSQL
    • Progress, Apama, and DataDirect
    • QlikTech and QlikView
    • SAND Technology
    • SAP AG
    • SAS Institute
    • ScaleDB
    • Software AG
    • solidDB
    • StreamBase
    • Sybase
    • Tableau Software
    • Talend
    • Teradata
    • Tokutek
    • Truviso
    • Vertica Systems
    • VoltDB and H-Store
  • Data integration and middleware
    • Application servers
    • EAI, EII, ETL, ELT, ETLT
  • Data types
    • GIS and geospatial
    • Native XML
    • Object
    • RDF and graphs
    • Text
  • DBMS product categories
    • Archiving and information preservation
    • Data warehouse appliances
    • Mid-range
    • OLTP
    • Open source
  • Emulation, transparency, portability
  • Fun stuff
    • Humor
  • Market share
  • Memory-centric data management
    • Cache
    • Complex event processing (CEP)
    • In-memory DBMS
  • Michael Stonebraker
  • Parallelization
    • MapReduce
  • Presentations
  • Pricing
  • Software as a Service (SaaS)
    • Cloud computing
  • Specific users
    • eBay
    • Facebook and Cassandra
    • Fox and MySpace
    • TEOCO
    • Yahoo
  • Storage
    • Solid-state memory
  • Theory and architecture
    • Columnar database management
    • Data models and architecture
    • Database compression
    • Database diversity
    • Petabyte-scale data management
  • TransRelational
  • Uncategorized

• Date archives

  Select Month July 2009  (6) June 2009  (25) May 2009  (19) April 2009  (30) March 2009  (23) February 2009  (29) January 2009  (18) December 2008  (10) November 2008  (13) October 2008  (29) September 2008  (60) August 2008  (28) July 2008  (23) June 2008  (7) May 2008  (16) April 2008  (18) March 2008  (22) February 2008  (25) January 2008  (35) December 2007  (18) November 2007  (12) October 2007  (31) September 2007  (16) August 2007  (11) July 2007  (9) June 2007  (16) May 2007  (6) April 2007  (18) March 2007  (17) February 2007  (8) January 2007  (13) December 2006  (1) November 2006  (1) October 2006  (7) September 2006  (17) August 2006  (6) July 2006  (12) June 2006  (1) May 2006  (7) April 2006  (7) March 2006  (2) February 2006  (4) January 2006  (13) December 2005  (9) November 2005  (9) October 2005  (10) September 2005  (1) August 2005  (6)

• Links

  • Monash Research
  • Webcasts
  • White Papers

• Admin

  • Log in

• Home
• About
• Contact
• Feeds