ParAccel: All content tagged as ParAccel in NoSQL databases and polyglot persistence
Monday, 27 May 2013
Amazon Redshift Update
A couple of interesting points from Werner Vogels’s post about Amazon Redshift’s security:
- Amazon Redshift has over 1000 customers and adding new ones at a rate of 100/week. I’m not familiar with customer acquisition numbers in the data warehouse space, but this doesn’t look like ParAccel, at least in its Redshift incarnation, is failing
- Amazon Redshift positioning: “price, performance and simplicity”. I cannot see many companies being able to compete against this triplet.
- Amazon has reduced the cost of read operations from DynamoDB to 1/4 to make that data more accessible to Redshift
Original title and link: Amazon Redshift Update (©myNoSQL)
via: http://www.allthingsdistributed.com/2013/05/amazon-redshift-designing-for-security.html
Wednesday, 22 May 2013
I expect ParAccel to fail too - Curt Monash
Curt Monash about the his prediction of ParAccel’s future failure:
Reasons include:
- ParAccel’s small market share and traction.
- The disruption of any acquisition like this one.
- My general view of Actian as a company.
One thing to keep in mind: ParAccel also hasAmazon as investors and it is in production behind the Amazon Redshift service. That’s a lot of visibility.
Original title and link: I expect ParAccel to fail too - Curt Monash (©myNoSQL)
via: http://www.dbms2.com/2013/04/25/goodbye-vectorwise-farewell-paraccel/
Monday, 20 June 2011
Columnar DBMS Vendor Customer Metrics
Very interesting customer base numbers for Sybase IQ, Vertica, SAND Technology, Infobright published by Curt Monash—most are in the hundreds, except for Sybase IQ.
This got me thinking what numbers would NoSQL companies have—is any of them sharing such numbers?. I’d speculate that most of them are in the tens, with 10gen (MongoDB) leading the space with probably a couple of hundreds at best.
Original title and link: Columnar DBMS Vendor Customer Metrics (NoSQL database©myNoSQL)
Tuesday, 22 March 2011
Types of Big Data Work
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)
