Larry Dignan summarizing a research by a Cowen analyst:
We believe the trend in compute is massively distributed commodity boxes,
and while there is a market for products like HANA and Exadata, it is
significantly smaller than optimistic descriptions by SAP and Oracle. We
believe HANA revenue is being inflated by subjective product revenue
allocation to HANA at the expense of its traditional Apps and BI businesses,
and swapping HANA for unused licenses. We think this inflates seat count
with no incremental cash to the firm. At some point investors will likely
start to worry about the implications on the other 90% of license sales we
expect will eventually turn negative. We believe the offense in this case is
getting into the data management business with old product (Sybase) and high
priced hardware (HANA). While the impact on the model is low, the
reputational cost to management could be high.
I have to confess that I’ve never really understood what these estimations are built upon. Maybe if I got this, I’d start calling myself an analyst.
Original title and link: The Market for Products Like HANA and Exadata ( ©myNoSQL)
Davy Suvee showing that Datablend’s custom datastore could deliver better performance than generic solutions like Hadoop, Vertica, or ExaData:
Although Vertica and Oracle’s results are impressive, they require a
significant hardware setup of 4 nodes, each containing 96GB of RAM
and 12 cores. My challenge: beating the Big Data vendors at their
own game by calculating triangles through a smarter algorithm that
is able to deliver similar performance on commodity hardware (i.e.
my MacBook Pro Retina).
Considering the size of the data (86mil. relationships), I wonder what the result would be using a graph database like Neo4j. Anyone up for testing it?
Original title and link: Counting Triangles Smarter (Or How to Beat Big Data Vendors at Their Own Game) ( ©myNoSQL)
There’s been a lot of speculation about the announcements coming from Oracle’s OpenWorld event. A first part was revealed during the keynote in the form of an in-memory analytics appliance called Exalytics . But there’s talk about a Big Data Appliance and an Oracle NoSQL database.
Here’re my predictions
Oracle became very aggressive in selling products based on hardware, software, and services. So they’ll announce a Hadoop appliance integrated with an existing Oracle product. It could be either the Oracle Exadata or even the newly announced Exalytics.
This appliance will place Oracle in competition with all other Hadoop appliance sellers: EMC, NetApp, IBM. Also these days most of the analytics databases try to integrate with Hadoop.
Oracle already has a couple of non-relational solutions in their portfolio: BerkleyDB, TimesTen, Coherence. And they’ve already started to test the NoSQL market by announcing the MySQL and MySQL Cluster NoSQL hybrid systems.
I don’t expect Oracle NoSQL database to be a new product. Just a rebranding or repackaging of one of the above mentioned ones. Probably the TimesTen.
Oracle will invest more into integrating its line of products with Hadoop. Having both a Hadoop and an in-memory analytics appliance will make them very competitive in this space.
Oracle will extend the support for NoSQLish interfaces (memcached) to its other database products.
What are your predictions?
Original title and link: The Oracle NoSQL Database and Big Data Appliance ( ©myNoSQL)
I agree this title is misleading but problem is clear: today Oracle does not provide any product can compete with new cloud computing needs and with the NoSQL movement. It is not possibile to think that actually the RAC technology of oracle can be used in a cloud environment and also a cloud service cannot be deployed over an Exadata.
The real question though is if Oracle is really interested by the market currently served by NoSQL databases and/or hybrid solutions. And judging by the latest versions of MySQL and MySQL Cluster it looks like they are testing the waters.
Original title and link: Will Oracle Win the NoSQL Competition ( ©myNoSQL)
Goldmacher estimated that YouTube consumption—user uploads of 48 hours of video a minute and 3 billion videos a day along with roughly 45 petabytes of viewed videos a day—would require at least 9 full-rack Exadata machines at $1.5 million each. There would be at least 18 Exadata machines to handle spikes. Those machines would add up to 14 Exalogic devices to serve data at $1.1 million per system. The software stack under Oracle would include WebLogic middleware, Oracle databases, Exadata optimized storage and Oracle as operating system. The open source comparison included JBoss middleware, MySQL, Hadoop and Red Hat Enterprise Linux as the OS.
Credit Peter Goldmacher (Cowen & Co. analyst)
Two comments (the only I have):
- what advantages would the enterprise stack offer to justify a 5x cost?
- in case all numbers are completely wrong, what’s the advantage of the enterprise stack?
Original title and link: Enterprise Big Data Stack vs Open Source Big Data Stack ( ©myNoSQL)
Mike Minelli: Working with big data can be classified into three basic categories […] One is information management, a second is business intelligence, and the third is advanced analytics
Information management captures and stores the information, BI analyzes data to see what has happened in the past, and advanced analytics is predictive, looking at what the data indicates for the future.
There’s also a list of tools for BigData: AsterData (acquired by Teradata), Datameer, Paraccel, IBM Netezza, Oracle Exadata, EMC Greenplum.
Original title and link: Types of Big Data Work (NoSQL databases © myNoSQL)