OCLC has been using HBase since 2012 to enable single-search-box access to over a billion items from your library and the world’s library collection. This talk will provide an overview of how HBase is structured to provide this information and some of the challenges they have encountered to scale to support the world catalog and how they have overcome them.

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Cloudera’s Vision for HBase
Krishna Maheshwari
Director, Product Management

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Where are we today
With bulleted list
• #17 DBMS by popularity1, #5 by revenue2
• Large ecosystem (Nifi, Kafka, Sqoop, Hive,
Impala, SOLR, Ranger, Atlas, etc)
• Supports NoSQL, SQL, Geospatual, Graph,
TimeSeries, Key Value and other use cases
• Sold by: Cloudera, IBM, Microsoft, Amazon,
Teradata, Oracle and more
1. As per db-engines
2. Cloudera anlaysis

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What has HBase enabled?
• Operationalizing ML / AI to revolutionize
healthcare, public utilities, etc
• Serving webscale content
• Empowering big data analytics for operational
and offline uses
• Acting as a resilient store of record

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What’s changed since HBase began
• Acceptable trade-offs
– Agility vs ownership
– Simplicity vs control
• Infrastructure as code
• Rise of “HTAP” systems
• Everyone offers NoSQL
Big data getting bigger

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Next 10 years
• Auto-resiliency, auto-scaling
• Self-optimization through AI/ML
• Multi-modal
• Performance

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User complaints can act as guideposts
• Hard to setup
• Complex to configure and tune
• Not quite multi-tenant
• Slow at analytics
• Doesn’t scale-up

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Where will Cloudera focus?
• Operational use cases
• Integration
• Infrastructure as code
• Performance

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THANK YOU