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page© 2015 VoltDB
REAL-TIME BIG DATA ANALYTICS IN THE IBM
SOFTLAYER CLOUD WITH VOLTDB
1
page© 2015 VoltDB
OUR SPEAKERS
John Hugg
Founding Engineer
VoltDB
2
Pethuru Raj Chelliah
Infrastructure Architect
IBM Soft...
page© 2015 VoltDB
THE VOLTDB ARCHITECTURE FOR FAST DATA
ü Per-machine performance + shared nothing scale out
ü Millions ...
page© 2015 VoltDB© 2015 VoltDB
THE MODERN OPERATIONAL APPLICATION
Ingest
Analyze
Decide
Streaming Analytics
Transactions
}...
page© 2015 VoltDB
1ST GENERATION FAST DATA: STREAMING ANALYTICS
• Examples:
Spark Streaming, Storm, Kinesis, CEP (Streamba...
page© 2015 VoltDB
2ND GENERATION FAST DATA:
COMBINE STREAMING ANALYSIS WITH THE OPERATIONAL STORE
• Operational workloads ...
page© 2015 VoltDB
FAST DATA PIPELINE
Export
VoltDB
Customer-Facing
-  Personalization
-  Customer experience
Operations-Fa...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Global Technolog...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Agenda
§  The I...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
The Top Disrupti...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
The Prominent Im...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
What to do with ...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Why Data Analyti...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
VoltDB for Real-...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
The Big Picture
...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
How VoltDB elimi...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
The Data Archite...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
VoltDB on IBM So...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters19
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Global Technolog...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
VoltDB installat...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Application main...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Connecting VoltD...
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters24
IBM/MTA Confidential | Cloud POC
© 2014 IBM CorporationGlobal Technology Services
innovation that matters
Thanks for liste...
page© 2015 VoltDB
QUESTIONS?
•  Use the chat window to type in your questions
•  Try VoltDB yourself:
Ø  Free trial of th...
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Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB

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Real-time analytics on streaming data is a strategic activity. Enterprises that can tap streaming data to uncover insights and take action faster than their competition gain business advantage. Join John Hugg, Founding Engineer, VoltDB and Pethuru Raj Chelliah and Skylab Vanga, Infrastructure Architect and Specialists, IBM SoftLayer to learn how VoltDB enables high performance and real-time big data analytics in the IBM SoftLayer cloud.

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Real-time Big Data Analytics in the IBM SoftLayer Cloud with VoltDB

  1. 1. page© 2015 VoltDB REAL-TIME BIG DATA ANALYTICS IN THE IBM SOFTLAYER CLOUD WITH VOLTDB 1
  2. 2. page© 2015 VoltDB OUR SPEAKERS John Hugg Founding Engineer VoltDB 2 Pethuru Raj Chelliah Infrastructure Architect IBM SoftLayer Skylab Vanga Infrastructure Architect IBM SoftLayer
  3. 3. page© 2015 VoltDB THE VOLTDB ARCHITECTURE FOR FAST DATA ü Per-machine performance + shared nothing scale out ü Millions of SQL statements per second per machine ü Up to 500k ACID-Transactional write proc calls per sec ü Full disk durability and sync cluster replication for HA ü Powerful tools for streaming analytics ü  Continuous queries, correlation, windowing, aggregation… ü Hadoop ecosystem integration VoltDB is really different than everything else
  4. 4. page© 2015 VoltDB© 2015 VoltDB THE MODERN OPERATIONAL APPLICATION Ingest Analyze Decide Streaming Analytics Transactions } } Fast Data =
  5. 5. page© 2015 VoltDB 1ST GENERATION FAST DATA: STREAMING ANALYTICS • Examples: Spark Streaming, Storm, Kinesis, CEP (Streambase, Esper, etc…), et al • Technical: • Lacks integrated “state” for transaction processing (operational) • Complex programming model • No ability to do ad hoc queries • Functional: • 1st Gen. only offers streaming analytics on windows of events • Separate database required for any meaningful work • Proprietary interface is inconsistent with the rest of the data pipeline • Does not support applications requirement for interaction 1stGen Streaming Stream Analytics Query Predefined
  6. 6. page© 2015 VoltDB 2ND GENERATION FAST DATA: COMBINE STREAMING ANALYSIS WITH THE OPERATIONAL STORE • Operational workloads want to understand data as it changes • Stream processing work needs state to enable richer analytics • Operations and Stream Processing are set to converge • Convergence is necessary to use streaming analysis in real- time • Automated application interactions are informed by data • Brings the application into the “data analytics” world • Streaming Analytics alone is passive, Fast Data is interac,ve     1stGen2ndGen Streaming Stream Analytics Query Predefined Ad hoc Support Operational Work VoltDB
  7. 7. page© 2015 VoltDB FAST DATA PIPELINE Export VoltDB Customer-Facing -  Personalization -  Customer experience Operations-Facing -  Network optimization -  API monitoring -  Sensors Batch/Iterative Analytics -  Statistical correlations -  Multi-dimensional analysis -  Predictive analytics Data at Rest Streaming Analytics -  Filtering -  Windowing -  Aggregation -  Enrichment -  Correlations Operational Interaction/ Transactions -  Context-aware -  Personal -  Real-time + Data in Motion
  8. 8. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Global Technology Services © 2014 IBM CorporationIBM/MTA Confidential | Cloud POC Real-time Analytics by VoltDB on IBM SoftLayer Cloud
  9. 9. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Agenda §  The IT Trends §  About VoltDB §  The Reference Architectures §  A Simple Demo 9
  10. 10. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters The Top Disruptive Transformations •  Digitization & Deeper Connectivity leads to massive amounts of Data •  Data Analytics technologies and tools enables data to information and to knowledge •  Knowledge-filled up Services and Applications for the Envisioned Smarter Planet 10
  11. 11. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters The Prominent Implications §  Trillions of Digitized Objects through digitization and edge technologies §  Billions of connected devices through deeper connectivity and service-enablement of physical, mechanical, electrical, electronics and IT systems §  Millions of software services (device-specific as well as agnostic) §  Zettabytes of multi-structured data §  Newer Analytical Capabilities – prognostic, predictive, prescriptive and personalized insights §  Cognitive Systems 11 The Prominent Challenges §  Hyper-converged Data Analytics Platforms §  Analytics-aware IT Infrastructures
  12. 12. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters What to do with the bulging data? § Indulge in analytics to extract insights § Implement Insights-driven Applications 12
  13. 13. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Why Data Analytics is vital? Data analytics is a process for squeezing out actionable insights out of data towards tactical and strategic decision-enablement for individuals as well as institutions Insights 1.  Enabling business Process Innovation 2.  Exploring fresh avenues for fresh revenues 3.  Elevating business efficiency and value 4.  Enhancing business operations, retaining customer loyalty, attaining newer customers, 5.  Expounding outside-in thinking in product designs 13
  14. 14. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters VoltDB for Real-time Data Analytics §  VoltDB is an in-memory scale-out database built to power the next generation of streaming data applications. §  VoltDB’s modern architecture provides fast data ingestion and export with massive scalability, real-time analytics, and data enrichment. §  VoltDB is a relational database system (RDBMS) for high-throughput, operational applications requiring: Ø  Orders of magnitude better performance than a conventional DBMS Ø  SQL as the native data language Ø  ACID transactions to ensure data consistency and integrity Ø  Built-in high availability (database fault tolerance) Ø  Database replication (for disaster recovery) 14
  15. 15. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters The Big Picture 1 5
  16. 16. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters How VoltDB eliminates the RDBMS Problems for real-time analytics §  Data and associated processing are partitioned together and distributed across the CPU cores (“partitions”) of a shared-nothing hardware cluster. §  Data is held in main memory, eliminating the need for buffer management. §  Transactions execute sequentially in memory, eliminating the need for locking and latching. §  Synchronous multi-master replication provides built-in high availability. §  Command logging provides a high performance replacement for “write-ahead” data logging. 16
  17. 17. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters The Data Architecture for Fast and Big Data
  18. 18. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters VoltDB on IBM SoftLayer Cloud §  Ideally suited to streaming applications in the cloud. §  In addition to providing extremely fast ingest, VoltDB exports data at high speed to long-term analytics stores. 18
  19. 19. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters19
  20. 20. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Global Technology Services © 2014 IBM CorporationIBM/MTA Confidential | Cloud POC A Simple Demo on IBM SoftLayer Cloud 20
  21. 21. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters VoltDB installation 21
  22. 22. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Application main page 22
  23. 23. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Connecting VoltDB Server 23
  24. 24. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters24
  25. 25. IBM/MTA Confidential | Cloud POC © 2014 IBM CorporationGlobal Technology Services innovation that matters Thanks for listening 25
  26. 26. page© 2015 VoltDB QUESTIONS? •  Use the chat window to type in your questions •  Try VoltDB yourself: Ø  Free trial of the Enterprise Edition: •  www.voltdb.com/Download Ø  Open source version is available on github.com •  Email us your question: askanengineer@voltdb.com 26

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