How other entrepreneurs approach growth and then go forth and make your business a runaway hit.
New Zealand-based Apple carrier Spark used robots to queue for the much coveted device.
Digital Transformation is here and that means everyone must embrace the disruptions.
Public cloud providers choose CloudStack because it provides all of the capabilities required to deliver multi-tenant IaaS services.
Here’s our recap of what’s transpired with Apache Spark since our previous digest
Three waves of technological innovation
Analytic RDBMS are still best-of-breed for supporting demanding BI
Who are the most influential Java people in the Twittersphere?
Only a little more than one in three of the three-dozen companies that we studied met the objectives of their analytics initiatives over the long term
A personalized video channel for Apple TV has now closed on $2.3 million in seed funding
The challenges of big data: Volume Variety Velocity Veracity
What makes you a sought after professional on the job market?
Indicators suggest Spark's popularity is still waxing.
MapR announced a $50 million equity financing today and revealed that it’s considering an initial public offering.
The use of Hadoop-based open source big-data technology continues to grow among enterprises.
Predictions on the future of Big Data
Potential of Big Data in the Indian Market
Get ready for Europe’s largest big data community gathering dedicated to Apache Spark!
Discussions of NoSQL DBAs and some things about DataStax and Cassandra themselves
If you cannot increase the power of a new generation of chips every few years then this business model collapses.
Apache Spark 2.0 adds the first version of a new higher-level API (Structured Streaming) for building continuous applications.
Spark Streaming has become one of the most widely used distributed streaming engines.
Which of the two data analytics engines is the better performer when it comes to applications in business.
We’re excited to announce the general availability of Apache Spark 2.0 on Databricks.
We continue to learn about Big Data through successful trial and error followed by production implementation.
Apache Spark 2.0 has become easier and faster and accessible to all.
The Connector provides a more natural development experience for Spark users.
Kafka is working really well for lots of companies. But it still has some rough edges.
The Databricks cloud implementation of Apache Spark simplifies the use of the open-source big data processing engine
how Hadoop fits in the industry and what other tools work well for big data streaming and batch processing
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Consensus 2016 will define what is “real” in blockchain technology and focus on how to mainstream real-world applications for consumers.