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Modern Big Data > Hadoop

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Modern Big Data > Hadoop

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Microservices! They are everywhere, or at least, the term is. When should you use a microservice architecture? What factors should be considered when making that decision? Do the benefits outweigh the costs? Why is everyone so excited about them, anyway?  Brought to you in partnership with IBM.

That's right. A modern big data solution requires more than Hadoop. Welcome to the data, it's all big and fast.

Welcome to Big Data Central

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I'm excited to announce that Big Data Central is live!

It represents my big data story for Couchbase. It's about the role of NoSQL databases in a world of big data.

There was a time when big data was Hadoop. It was offline analytics. That's no longer the case. It's a solution. It's a solution that includes Hadoop but is not Hadoop. It's a solution that meets both real-time analytical requirements and offline analytical requirements. It's a solution that meets both analytical requirements and operational requirements.

The big data ecosystem now includes Storm for real-time processing, Couchbase Server for high performace data access, Hadoop for offline analytics, and more!

There are three big data challenges:

  1. The amount of data being generated, data volume.
  2. The rate at which data is being generated, data velocity.
  3. The rate at which information must be generated, information velocity.

Hadoop addreses data volume. It can store and process a lot of data, later. It scales out to store and process more data. Hadoop does not address data velocity. However, it meets offline analytical requirements.

Couchbase Server addresses data velocity. It is a high performance NoSQL database that can store a lot of data, now. It scales out to store a lot of data, faster. Couchbase Server does not address information velocity. It can store and process data at rest. However, it meets operational requirements.

Storm addresses information velocity. It can process a real-time stream of data. It scales out to process streams of data, faster. Storm does not address volume or data velocity. It does not store data. It processes data in motion. However, it meets real-time analytical requirements.

All three big data challenges can be met by integrating Storm, Couchbase Server, and Hadoop. By integrating Couchbase Server with storm, a real-time stream of data can be processed and stored. By integrating Couchbase Server with Hadoop, a lot of data can be processed offline.

Discover how the Watson team is further developing SDKs in Java, Node.js, Python, iOS, and Android to access these services and make programming easy. Brought to you in partnership with IBM.


Published at DZone with permission of Shane Johnson, DZone MVB. See the original article here.

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