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6 Reasons Big Data Requires Rethinking Your Middleware
Greg Barron 14 March 2013
Transcript of 6 Reasons Big Data Requires Rethinking Your Middleware
Your Middleware It takes new tools and technologies to make the most of big data. Sensor networks, social networking and mobile computing are driving a flood of real-time information. 1 Elastic scalability isn’t just for storage and processing power. Big data creates unpredictable data flows that can quickly overwhelm your existing application infrastructure. Your middleware needs to be as dynamically scalable as the rest of your big data architecture. Your middleware needs to scale without sacrificing reliability or spurring datacenter sprawl. 3 The flood of information big data enables can be hard to handle, especially by consumers that are linked by slower networks, can’t keep up with bursts of data, or only connect periodically to retrieve updates. You need to elegantly handle
the delayed delivery of messages to slow consumers without affecting those that can consume the full real-time feed. 4 Big data doesn’t just live wherever your Hadoop or Cassandra clusters are running, it’s generated and consumed by applications and users around the world. Your middleware must be able to efficiently distribute data globally via WANs, the Web and mobile apps. 5 Big data apps demand 24x7x365 availability even through natural disasters and other unforeseen circumstances. Your middleware needs to automatically recover from system faults and even datacenter-level outages. 6 To learn how leading companies like yours are using Solace to accelerate and reduce the complexity of their big data initiatives, go to Continuously patching your infrastructure to keep up with growing data volumes and changing requirements leads to a complicated and fragile system. Solace’s appliances address all of these challenges with 10-30 times higher throughput than alternatives, with superior robustness and scalability, all for a fraction of the cost. http://solacesystems.com/bigdata IDC estimates that the amount of digital data in the world is more than doubling every two years. 2011 Digital Universe Study:
Extracting Value from Chaos If you try to support big data by scaling yesterday’s middleware, your datacenter will spiral out of control in terms of robustness, rack space, power consumption and complexity. 2 6 Your middleware should be based on a simple, stable architecture that’s easy to adapt as your needs evolve. It takes a new breed of middleware to capitalize on big data. Let’s examine six middleware challenges hidden within the big data opportunity.