Navigating the NoSQL Landscape, Sun Seng David TAN, Serli

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In the era of cheap disk space, processing power and high bandwidth networks, the constraints that caused our industry to have a near exclusive focus on Relational Database Management Systems (RDBMS) have abated. The terminology surrounding NoSQL and BigData are confusing to IT professionals trying to select the right storage for the right problem. The talk will explore the technical reasons you might select one of these new databases, the types of databases available, their correct use and quintessential use cases for them. Also discussed will be the counter indications for them. This is a survey talk for management and developers who are new to NoSQL/BigData/Non-RDBMS.

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Navigating the NoSQL Landscape, Sun Seng David TAN, Serli

  1. 1. The NoSQL Landscape Sun Seng David TAN SERLI
  2. 2. What we’ll talk about • Why RDBMS are not enough? • What are the different NoSQL taxonomies? • Which “NoSQL” is right for me? Serli
  3. 3. Growth is the New Reality • Instagram gained nearly 1 million users overnight when they expanded to Android Serli
  4. 4. Does it work with RDMBS backend? Application Scales Out Just add more commodity web servers Database Scales Up Get a bigger, more complex server Note – Relational database technology is great for what it is great for, but it is not great for this.
  5. 5. NoSQL database matches application logic tier architecture Data layer now scales with linear cost and constant performance Application Scales Out Just add more commodity web servers NoSQL Database Servers Database Scales Out Just add more commodity data servers Scaling out flattens the cost and performance curves. Serli
  6. 6. NoSQL catalog Cache (memory only) Key-Value Data Structure Memcached Document Column Graph Redis Couchbase Cassandra Neo4j MongoDB HBase Database (memory/disk) Coherence Membase InfiniteGraph
  7. 7. What about Hadoop?
  8. 8. Conclusion • One Size Does Not Fit All • Overview of the the NoSQL types • Choose the right solution – Developer Productivity – Large Scale Data Serli
  9. 9. Q&A
  10. 10. Thanks!

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