Two weeks ago I wrote about "The Need for Speed" in cloud computing, and
asked "Who is going to build the low-latency cloud for enterprise
customers?". Today Werner Vogels and his team at Amazon announced their
Cluster Compute Instances offering.
This is a very important step forward towards the kind of realtime, high
performance cloud that customers such as Cloudscale require to deliver the
next generation of cloud services. In our case, it means we now have three
distinct alternatives for deployment of our massively parallel realtime data
warehouse architecture: standard public cloud (EC2+S3+...), in-house cluster
(Eucalyptus or native), and now high-performance public cloud cluster.
As a former parallel supercomputing researcher, turned realtime analytics
guy, I'm excited and impressed by what Werner and his team are opening up
today. Just as commodity clusters hav... (more)
Bill McColl's "Cloud N" Blog
This is an incredibly important time for the cloud computing area. But
let’s try and move the discussion of it in the press along from an
obsession with new datacenter buildings located by power stations, with the
total server numbers at Microsoft and Google, and with Amazon’s hourly
pricing for EC2. Interesting though those aspects of cloud computing appear
to be to journalists, they hardly represent what is really industry changing
about cloud computing.
What are some of the new directions in the massively parallel cloud computing
space? I’ll mentio... (more)
Cloud Data Analytics on Ulitzer
In the previous article we looked at how realtime cloud analytics looks set
to disrupt the $25B SQL/OLAP sector of the IT industry. What are users
looking for from a next-generation post-SQL/OLAP enterprise analytics
solution? Let's look at the requirements:
Realtime + Historical Data. In addition to analyzing (historical) data held
in databases (Oracle, SQLServer, DB2, MySQL) or datastores (Hadoop, Amazon
Elastic MapReduce), a next-gen analytics solution needs to be able to
analyze, filter and transform live data streams in realtime, with low
For twenty years, analytics has been viewed as just one specific area within
the broader relational database industry. So, analytics has meant databases.
Today that view is changing. Over the past year or so, a new movement, the
"NoSQL" movement has emerged promoting the advantages of doing a variety of
kinds of analytics without using any relational database technologies at all.
Whatever one thinks of the capabilities and limitations of distributed
key-value stores relative to relational databases, one thing is clear - the
stranglehold that SQL has held over all aspects of data an... (more)
Cloudcel on Ulitzer
Back in 1985, the world was pre-web, data volumes were small, and no one was
grappling with information overload. Relational databases and the shiny new
SQL query language were just about perfect for this era. At work, 100% of the
data required by employees was internal business data, the data was highly
structured, and was organized in simple tables. Users would pull data from
the database when they realized they needed it.
Fast forward to 2010. Today, everyone is grappling constantly with
information overload, both in their work and in their social life. Most ... (more)