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Big Data Journal: Blog Feed Post

Real-time Big Data or Small Data?

I’ve been asked what I consider as “Big Data” versus “Small Data” in this domain. Here’s my view.

Have you heard of products like IBM’s InfoSphere Streams, Tibco’s Event Processing product, or Oracle’s CEP product? All good examples of commercially available stream processing technologies which help you process events in real-time.

I’ve been asked what I consider as “Big Data” versus “Small Data” in this domain. Here’s my view.

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Real-Time Analytics Small Data Big Data
Data Volume None None
Data Velocity 100K events / day (<<1K events / second) Billion+ events / day (>>1K events / second)
Data Variety 1-6 unstructured on sources AND 1 single destination (an output file, a SQL database, a BI tool) 6+ structured and 6+ unstructured for sources AND many destinations (a custom application, a BI tool, several SQL databases, NoSQL databases, Hadoop)
Data Models Used for “transport” mainly. Little to no ETL, in-stream analytics, or complex event processing performed. Transport is the foundation. However, distributed ETL, linearly scalable in-memory and in-stream analytics are applied, and complex event processing is the norm.
Business Functions One line of business (e.g. financial trading) Several lines of business – to – 360 view
Business Intelligence No queries are performed against the data in motion. This is simply a mechanism for transporting transaction or event from the source to a database.Transport times are <1 second.

 

 

Example: connect to desktop trading applications and transport trade events to an Oracle database.

ETL, sophisticated algorithms, complex business logic, and even queries can be applied to the stream of events as they are in motion.  Analytics span across all data sources and, thus, all business functions.Transport and analytics occur in < 1 second.

 

Example: connect to desktop trading applications, market data feeds, social media, and provide instantaneous trending reports. Allow traders to subscribe to information pertinent to their trades and have analytics applied in real-time for personalized reporting.

Want to see my view of Batch Analytics? Go Here.

Want to see my view of Ad Hoc Analytics? Go Here.

Here are a few other products in this space:

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More Stories By Jim Kaskade

Jim Kaskade is CEO of Infochimps. Before that he served as SVP and General Manager at SIOS Technology, a publicly traded firm in Japan, where he led a business unit focused on developing private cloud Platform as a Service targeted for Fortune 500 enterprises. He has been heavily involved in all aspects of cloud, meeting with prominent CIOs, CISOs, datacenter architects of Fortune 100 companies to better understand their cloud computing needs. He also has hands-on cloud domain knowledge from his experience as founder and CEO of a SaaS company, which secured the digital media assets of over 10,000 businesses including Fortune 100 customers such as Lucasfilm, the NBA, Sony BMG, News Corp, Viacom, and IAC. Kaskade is also one of the Top 100 bloggers on Cloud Computing selected by the Cloud Computing Journal.