This document summarizes a presentation about fueling business with real-time analytics. It discusses MemSQL, a real-time database for transactions and analytics, and how it can be used with Spark for various use cases like operationalizing models, stream processing, dashboards, and geospatial analytics. MemSQL allows ingesting and querying large amounts of geospatial data in real-time at scale, unlike traditional databases. The presentation provides examples of using MemSQL with geospatial and taxi trip data to enable real-time location intelligence applications.
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From Spark to Ignition: Fueling Your Business on Real-Time Analytics
1. Fueling Your Business on Real-Time Analytics
Eric Frenkiel, MemSQL CEO
March 30, 2015 • Las Vegas, NV
From Spark to Ignition:
2. What’s in Store For This Presentation?
1. MemSQL:
A real-time database for transactions and analytics
2. Spark Use Cases
3. Example: Geospatial Enhancements
4. MemSQL Snapshot
Experienced Leadership
• Microsoft, Facebook, Oracle, Fusion-io
Inspired by Enterprise architecture gap
A real-time database for transactions
and analytics
• In-memory, distributed, SQL
Broad customer adoption across verticals
Top tier investors
5. Four Ways Your DBMS is Holding You Back
ETL (Extract, Transform, Load)
Analytic Latency
Synchronization
Copies of data
Source: Gartner Hybrid/Transactional/Analytical Processing Will Foster Opportunities for Dramatic Business Innovation
6. The Real-Time Database for Transactions and Analytics
Highest Value
Hot Data
High Value
Cold Data
Analytics
Transactions
Data Loading and Queries
Aggregator Nodes
Availability
Group 1
Availability
Group 2
Cluster
7. Gartner Identifies Emerging Category:
HTAP (Hybrid Transactional/Analytical Processing)
“HTAP will enable business
leaders to perform…much
more advanced and
sophisticated real-time
analysis of their business
data than with traditional
architectures.”
Download at: memsql.com/gartner
8. Simple
Standard SQL
Transactions and analytics in one database
Behind the firewall or on the cloud
Flexible integrations (Hadoop, Spark, SQL)
14. MemSQL and Spark Use Cases
Operationalize models built in Spark
Stream and event processing
Live dashboards and automated reports
Extend MemSQL analytics
15. Operationalize Models Built in Spark
Process in Spark, persist to MemSQL
Go to production and iterate faster
Enterprise
Consumption
Data into Spark
Model Creation Model Persistence
16. Stream and Event Processing
Structure event data on the fly
Pass to MemSQL for persistent, queryable format
Enterprise
Consumption
Real-time
Streaming Data
Data Transformation
Persistent,
Queryable Format
19. Extend MemSQL Analytics
The freshest data for analysis in Spark
Load from MemSQL to Spark and write results on return
Access to Live
Production Data
Real-time Replica
Applications,
Data Streams
Interactive
Analytics,
Machine Learning
20. Live Dashboards and Automated Reports
Serve live dashboards from MemSQL
Run custom reports on live data with Spark
Live
Dashboards
Custom
Reporting
Access to Live
Production Data
SQL Transactions
and Analytics
22. Geospatial Challenge
Commercial applications now geo-enabled
Location is everywhere
Lots of insight possible
Traditionally geo is processed separately
Real need for integrated geospatial at scale
24. MemSQL Geospatial
BILLIONS of objects
Sub-second latency
Geo data is first-class citizen
Geo + Simplicity + Speed + Scale
25. Real-Time Geospatial Location Intelligence
Sample from 170 million taxi trips
Real-time ingest
Concurrent queries in fractions of a second
Unlimited number of geographic views
Simple queries while simultaneously ingesting data
26.
27. Thank You!
Visit the MemSQL Booth #119
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