2015 Real-Time IT Trends in Retail and eCommerce

January 21st, 2015

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Jason Miller, Product Specialist

Conor Doherty, Technical Marketing

Agenda

▸Current Trends

▸Role of Innovative Technology

▸Live Demo on Retail Data

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Consumer expectations

are at an all-time high

The omni-channel user experience demands a

different approach

How to use innovative technology to meet these

demands and build real-time applications to

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Identify more opportunitiesBetter understand

customer activityIncrease customer value and satisfaction

Omni-Channel Goal: Seamless User Experience

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Specific Use Cases

Consumer alignment requires real-time analytics

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Advertising Recommendations

Loyalty Programs Dynamic Pricing

Legacy Omni-Channel Architecture

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RDBMS

system of record

(structured)

Compute

Servers

ETL/batch

transformation

Key Value Store

caching/serving

data

Data Warehouse

reporting

Applications

mobile, web, in-store POS

BI/Analytics

Interface

NoSQL Store

system of record

(semi-structured)

MemSQL Omni-Channel Architecture

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Applications

mobile, web, in-store POS

BI/Analytics

Interface

• SQL queries

• Spark

• Data

visualization

• system of record (structured + semi-structured)

• data transformations

• serving layer

• reporting

Gartner Market Guide for In-Memory DBMS

“Rapid technological advances in in-memory computing have led to the

emergence of hybrid transaction/analytical processing (HTAP)…This

enables real-time analytics and situation awareness on "live"

transaction data as opposed to after-the-fact analysis on "stale data”

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Gartner Recommends:

▸Pilot the uses of HTAP architectures

▸Task a small team of engineers and

business users to investigate

▸Run a proof of concept

Download at: memsql.com/gartner

MemSQL Customers

▸Web Applications

• Performance monitoring

• Fraud detection

• Recommendations

▸Ad Tech

• Real-time bidding and attribution

• Overlap Analysis

▸Financial Services

• Position Analysis

• Risk management

▸Event and Machine Data

• Machine data collection

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Simple Fast Scalable

• Standard SQL

• Transactions and

analytics in one

database

• Compatible with

traditional systems

• Flexible integrations

(Hadoop, Spark)

• Extremely low-latency

queries

• Massive parallel

transaction capacity

• Lock-free, shared-

nothing architecture

• Scales out on

commodity hardware

• Deploys to hundreds

or thousands of

machines

• Truly linear scaling

The New Model: Centralized Data Hub for Business

Operations

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Conclusion

▸Ingested retail data – Tens of millions of records

▸Examine this data to answer complex business questions

▸Demonstrated the ability of MemSQL to analyze data in

real-time

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Thank you

▸Free 30-day trial of MemSQL

▸www.memsql.com/download

▸Jason Miller

▸miller@memsql.com

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