big data hype or reality
Post on 05-Dec-2014
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Agenda
• What is Big Data?
• Technology Radar
• Technologies in scope.
• Architecture
• Wanted!
• Next steps.
The world of data is changing.
Data has a chaotic nature.
Big Data <> Big DataBig Data == Big in Data.
Big Data = 4 V’s.
Volume = Dealing with the size.
Variety =
Handling the multiplicity of types, sources and formats.
Velocity=
Reacting to the flood of information in the time required by the application.
Veracity =
How can we cope with uncertainty, imprecision, missing values or untruths.
Big Data 1.0=
Building the capabilities to process large dataIn support of their current operations
(efficiency improvement).
Big Data 2.0=
What can I now do that I couldn’t do before, or do better then I could do before.
Polyglot persistence
• Relational databases are not dead.
• Enterprises should expect multiple data-storage technologies for different applications.
• Even for a single application, polyglot persistence is good.
• Do not replace one database solution with another to expect wonders.
Technologies in the picture
• Hadoop and technologies build on top of it.
• ElasticSearch.
• neo4J.
Hadoop
• Apache Foundation
• Commercial solutions
• Hortonworks
• Cloudera
• MapR
And many more...
ElasticSearch
• Based on lucene.
• ElasticSearch is also the name of the company.
• Search, analyze and index in realtime.
• Distributed.
• High availability.
• Document-oriented.
• Schema free
• RESTful api
neo4j
• Graph database.
• Ideal for metadata and relationships.
• Not for large content.
• Not for large graphs.
Polyglot persistence
• Relational databases are not dead.
• Enterprises should expect multiple data-storage technologies for different applications.
• Even for a single application, polyglot persistence is good.
• Do not replace one database solution with another to expect wonders.
Next steps.
Learning and case study group.
I need datastores:- Openstreetmap.- NASA- ....
Q&A
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