SlideShare a Scribd company logo
Confidential – Restricted
Cloudera’s Vision for HBase
Krishna Maheshwari
Director, Product Management
Confidential – Restricted 2
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
Confidential – Restricted 3
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
Confidential – Restricted 4
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
Confidential – Restricted 5
Next 10 years
• Auto-resiliency, auto-scaling
• Self-optimization through AI/ML
• Multi-modal
• Performance
Confidential – Restricted 6
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
Confidential – Restricted 7
Where will Cloudera focus?
• Operational use cases
• Integration
• Infrastructure as code
• Performance
Confidential – Restricted
THANK YOU

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Managing the Dewey Decimal System

  • 1. Confidential – Restricted Cloudera’s Vision for HBase Krishna Maheshwari Director, Product Management
  • 2. Confidential – Restricted 2 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
  • 3. Confidential – Restricted 3 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
  • 4. Confidential – Restricted 4 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
  • 5. Confidential – Restricted 5 Next 10 years • Auto-resiliency, auto-scaling • Self-optimization through AI/ML • Multi-modal • Performance
  • 6. Confidential – Restricted 6 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
  • 7. Confidential – Restricted 7 Where will Cloudera focus? • Operational use cases • Integration • Infrastructure as code • Performance