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Real-Time Data Pipelines
Nikita Shamgunov, MemSQL CTO and co-founder
February 17, 2016
MemSQL Confidential2
Designed for Modern Hardware, Trends, and Workloads
Scalable SQL
In-Memory and
Solid-State
Distributed Datacenter or Cloud
 Multi-mode
 OLTP, OLAP, HTAP
 Multi-model
 ANSI SQL
 Key-value
 Document/JSON
 Geospatial
 In-Memory rowstore
 Solid-state columnstore
 Stream directly to
rowstore or columnstore
 Distributed query
optimizer and execution
 Scale-out on commodity
hardware
 Deploy on-premises
 Cloud agnostic
 Amazon
 Microsoft
 Google
 Digital Ocean
Simple Real-Time Affordable Flexible
SSD
3
Creating Real-Time Pipelines with Streamliner
Real-Time
Application
 One click deployment of integrated Apache Spark
 Create real-time data pipelines through a graphical UI
 Eliminate batch ETL
 Open sourced on GitHub at memsql.github.io/spark-streamliner
MemSQL Confidential
Apache Spark
STREAMLINER
Extract Transform Load
STREAMLINER
Real-Time
Inputs
MemSQL Confidential4
MemSQL in Energy
 Real-Time Scoring for Predictive Applications
 Sensor reading and predictive model score appear
simultaneously in database table
Input
User Jar
SAS Generated PMML
Industrial
Equipment
Sensor Data
S1 S2 S3 P1 P2 P3
Sensor 1 Predictive Model 1
STREAMLINER
Internet-of-Things simulation depicting health
of wind turbines globally.
7 machines - AWS C4-2X large instances, at
$0.311 per hour
per machine,
annual cost ~ $19,000.
MemSQL PowerStream
Sensors
Wind Turbine Wind Farm
MemSQL PowerStream
197,000 wind turbines around the world
Apache Spark
STREAMLINER
Data Producers
(simulating sensor
activity)
PowerStream User
Interface
MemSQL PowerStream Architecture
Thank You
www.memsql.com

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PowerStream Demo

  • 1. Real-Time Data Pipelines Nikita Shamgunov, MemSQL CTO and co-founder February 17, 2016
  • 2. MemSQL Confidential2 Designed for Modern Hardware, Trends, and Workloads Scalable SQL In-Memory and Solid-State Distributed Datacenter or Cloud  Multi-mode  OLTP, OLAP, HTAP  Multi-model  ANSI SQL  Key-value  Document/JSON  Geospatial  In-Memory rowstore  Solid-state columnstore  Stream directly to rowstore or columnstore  Distributed query optimizer and execution  Scale-out on commodity hardware  Deploy on-premises  Cloud agnostic  Amazon  Microsoft  Google  Digital Ocean Simple Real-Time Affordable Flexible SSD
  • 3. 3 Creating Real-Time Pipelines with Streamliner Real-Time Application  One click deployment of integrated Apache Spark  Create real-time data pipelines through a graphical UI  Eliminate batch ETL  Open sourced on GitHub at memsql.github.io/spark-streamliner MemSQL Confidential Apache Spark STREAMLINER Extract Transform Load STREAMLINER Real-Time Inputs
  • 4. MemSQL Confidential4 MemSQL in Energy  Real-Time Scoring for Predictive Applications  Sensor reading and predictive model score appear simultaneously in database table Input User Jar SAS Generated PMML Industrial Equipment Sensor Data S1 S2 S3 P1 P2 P3 Sensor 1 Predictive Model 1 STREAMLINER
  • 5. Internet-of-Things simulation depicting health of wind turbines globally. 7 machines - AWS C4-2X large instances, at $0.311 per hour per machine, annual cost ~ $19,000. MemSQL PowerStream
  • 6. Sensors Wind Turbine Wind Farm MemSQL PowerStream 197,000 wind turbines around the world
  • 7. Apache Spark STREAMLINER Data Producers (simulating sensor activity) PowerStream User Interface MemSQL PowerStream Architecture