Hadoop and NoSQL databases have emerged as leading choices by bringing new capabilities to the field of data management and analysis. At the same time, the RDBMS, firmly entrenched in most enterprises, continues to advance in features and varieties to address new challenges. Join us for a special roundtable webcast on April 7th to learn: The key differences between Hadoop, NoSQL and RDBMS today The key use cases How to choose the best platform for your business needs When a hybrid approach will best fit your needs Best practices for managing, securing and integrating data across platforms

1. Leveraging Big Data with Hadoop,
NoSQL and RDBMS
—
April 7, 2016
Brian Bulkowski

2. 2Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Sustainable Differentiators
SPEED AT SCALE
• Index in RAM, Data in Flash: Persistence
• Key-value store
• Open Source
SMART CLIENTS
• Ease of use for programmers
• Patented functionality that accelerates development by shielding
developers from low level programming
CLUSTERING
• Availability
• Patented clustering algorithms that solve the hardest problems of
distributed computing
TCO
• Optimized for Flash
• Demonstrated 10 to 1 price performance savings
• Battle tested, almost no downtime

3. 3Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
10X Faster or 10X Fewer

4. 4Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Polyglot Architecture
Transactions
(Compliance, Legacy)
(Oracle, DB/2,
SQLServer, MariaDB,
Postgres)
Operational
In-memory
(Fast, Scalable, HA)
(Aerospike, Cassandra
with Cache, Coherence)
Operational Analytics
Relational
Ad-Hoc
(Exadata, Aster,
Teradata)
Hadoop Big Data
(Cloudera, Hortonworks,
MapR)
Column
(Vertica, RedShift,
SnowFlake, Oracle)
Graph
(Neo4J, Objectivity,
... )
Streaming
(Spark, Heron)
… fast analytics but
still analytics
App server architecture
In-memory SQL
(VoltDB, MemSQL, …)
Polyglot Analytics systems (multiple are required because of
performance reasons –data layout matters)
Operational
In-memory
Read Write

5. 5Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Old Style Architecture Has Significant Limitations
Challenges
• Complex
• Maintainability
• Durability
• Consistency
• Scalability
• Cost ($)
• Data Lag
Caching Layer
Operational Database
Real-time
Consumer Facing
Pricing /
Inventory/Billing
Real-time
Decisioning
Streaming
Data
Legacy Database
(Mainframe)
RDBMS
Databas
e
Transactional
Systems
Enterprise Environment
Legacy RDBMS
HDFS BASED

6. 6Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
High Performance NoSQL Enables Real-time Applications
Real-time
Consumer Facing
Pricing /
Inventory/Billing
Real-time
Decisioning
Streaming
Data
Aerospike
Connectors
Legacy Database
(Mainframe)
RDBMS
Databas
e
Transactional
Systems
Enterprise Environment
XDR
Aerospike
Legacy RDBMS
HDFS BASED
Next Generation Operational Database
Business transactions of
500/sec X 2500 reads/writes/
calculations per business
transaction
= 1.25M Server
Transactions/sec
Speed at Scale, Predictable Performance, Highest Availability & Lowest TCO

7. 7Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Business Challenge
• Meet SLAs of 750 ms per business transaction
• Differentiate between fraudulent and legitimate orders in real-
time
• Support next-generation Machine Learning
• Stop loss of business due to latency
• Support hundreds of DB reads/writes per credit card
transaction
• Increase operational data 10x
Prevent Only Fraudulent Transactions

8. 8Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Selected Aerospike in-Memory NoSQL
• Built for Flash
• Predictable Low latency at
High Throughput
• Immediate consistency, no data loss
• Cross data center (XDR) support
• 20 Server Cluster
• Dell 730xd w/ 4NVMe SSDs
Prevent Only Fraudulent Transactions
Credit Card Processing System
Fraud Detection & Protection App
Rules
Rule 1
Rule 2
Rule 3
Historical Data
Rule 1-Passed
Rule 2-Passed
Rule 3-Failed
Account Behavior
Static Data
Account
Statistics

9. 9Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Intra-day System of Record
Challenge
• DB2 (RDBMS) stores positions for 10 Million customers
• Must update stock prices, show balances on 300 positions,
process 250M transactions, 2M updates/day
• Risk, System of Engagement and Mobile
• Data inconsistencies, long restarts, growing
number of servers, restarts take 1 hour

10. 10Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Intra-day System of Record
Selected Aerospike in-Memory NoSQL
• Built for Flash
• Predictable Low latency at High Throughput
• Immediate consistency, no data loss
• Hot standby implementation for extra redundancy
• Cross data center (XDR) support
• 10 Server Cluster
IBM DB2
(Mainframe)
Real-Time App Record App
Finance App
Real-Time
Data Feed
Start of the Day
Data Loading
End of Day
Reconciliation
Account
Positions

11. 11Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
AdTech – Predictive Analytics at Scale
Challenge
• Low read latency (milliseconds)
• 100K to 5M operations/second
• Ensure 100% uptime
• Provide global data replication
Performance achieved
• 1 to 6 billion cookies tracked
• 5.0M auctions per second
• 100ms ad rendering, 50ms real-time bidding,
1ms database access
• 1.5KB median object size
Selected Aerospike NoSQL over competition
• 10X fewer nodes
• 10X better TCO
• 20X better read latency
• High throughput at low latency
Ads is Displayed
Publishers
Ad Networks & SSPs
Ad Exchanges
Demand Side
Platform
Data Management
Platforms
Brands Agencies Buyers
0 ms 100 ms

12. 12Proprietary & Confidential || © 2015 Aerospike Inc. All rights reserved.[ ]
Telco – Real-Time Billing and Charging Systems
Challenge
• Edge access to regulate traffic
• Accessible using provisioning applications
(self-serve and through support personnel)
Need for extremely high availability,
reliably, low latency
• > TBs of data
• 10-100M objects
• 10-200K TPS
Selected Aerospike in-Memory NoSQL
• Clustered system
• Predictable low latency at high throughput
• Highly-available and reliable on failure
• Cross data center (XDR) support
SOURCE
DEVICE/USER DESTINATIONReal-Time
Auth. QoS Billing
Request Execute
Request
Real-Time ChecksConfig Module App
Update Device
User Setting
Hot-Standby
XDR

13. THANK YOU!
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