The Race to the Next Database: Overclocking and Analytics Augment Your Data Layer

A star studded panel on The Race to the Next Database: Overclocking and Analytics Augment Your Data Layer is next. Panelists include

* Mayank Bawa Aster Data Systems
* Doug Judd Zvents
* Luke Lonergan Greenplum
* Damian Black SQLstream
* Dave Schrader Teradata
* Scott Wiener Cloud9Analytics

Nitin Borwankar of TagSchema is moderating the session. He has an impressive background in databases. He used to be a J2EE consultant. He is focusing on what kind of problems are pain points for large scale web applications? In social applications you have many to many relationships.

Mayank Bawa: (CEO and founder of Aster Data Systems)

• Scalable database for warehousing and anaytics that runs on a cluster of commodity nodes
• founded in 2005
  
• colleagues from Stanford
• Investors
• Sequoia Capital
• Cambrian Ventures
• First Round Capital
• Sample Customers
• MySpace (they are the backend data warehousing engine)
• In one day MySpace more than 1 billion impressions per day which is loaded into aster
• every hour resulting in over 1 TB of new data
• 100 node Aster cluster
  
• Aggregate Knowledge

Doug Judd (Zvents)

• Google is arguably the king of data. They capture more data and analyze more data than anything in the world
• Google has developed three key pieces of infrastructure
• GFS
• MapReduce: Computation framework that works closely with GFS
• BigTable: Somewhat analogous to a traditional db except it is massively scalable.
• Hypertable
• Open Source implementation of BigTable
• pulls common scaling logic into a general distribution layer

Luke: (Greenplum)

• Took a traditional db architecture and twisted it into a massively parallel infrastructure
• Customers
• 40% of business came from Asia last quarter
• Leveraging PostgreSQL developers worldwide
• helped them get to more places
• Data is growing tremendously
• All sectors need to understand their data

Damian Black (SQLStream)

• Manages high volume streams
  
• SQLStream eliminates latency via a pipelined approach.
• SQL example

Dave Schrader Teradata

• $1.7 billion a year company
• WellsFargo, PayPal and many big companies are clients
• Founded in 1979
• First MPP db engine

Scott Wiener Cloud9Analytics

• focused on different part of market
• using Internet to deliver BI to unserved
  
• $50B in 2008 spent on BI
• business users still unsatisfied
• $6B on SaaS, expectations gap wider and growing fast
• deliver end-user analytical applications
  
• BI moving from on-premise to on-demand model
• they don't use databases or reporting
• Anytime, anyplace analytics
• using Flex

How is web disrupting databases?
MB: Everytime scale changes, we have to rethink scalability. Web allows for interactivity so feedback loop has to finish very fast.

DJ:Traditional db technology designed to run on a single machine. Web has massive amount of data that must scale. The problem of scaling one machine is exponentially more difficult.

LL: Google is making billions of advertising. Importance of data is more now. They are building 10-20 petabyte warehouse for a customer. It's become more important to solve those problems. They had to re-invent the concept of databases to drive the workload

DB: Real time decision making is built into their business.

SW: Web is speeding up pace of the business. A lot of decision making is being automated. When you automate, you need to be able to detect exceptions. Now technology drives business.

LL One thing they have focused on is data loading. They have a subscription based pricing model.