webinar: architectures for digital transformation and next-generation systems of engagement

1© 2016 Aerospike Inc. All rights reserved. [ ]

Architectures for Digital Transformation

and Next-Generation Systems of

Engagement

June 21, 2016


Noel Yuhanna - Principal Analyst,

Forrester Research

Brian Bulkowski, CTO and CO-

Founder, Aerospike

Speakers


Response time: Hours, Weeks

TB to PB

Read Intensive

TRANSACTIONS

(OLTP)

Response time: Seconds

Gigabytes of data

Balanced Reads/Writes

ANALYTICS (OLAP)

STRUCTURED

DATA

Response time: Seconds

Terabytes of data

Read Intensive

BIG DATA ANALYTICS

System of engagement

Response time: < 5 ms

1-100 TB

Balanced Reads/Writes

24x7x365 Availability

UNSTRUCTURE

D DATA

NoSQL

Database Landscape


Use Cases


LEGACY DATABASE

(Mainframe)

XDR

Decisioning Engine

DATA WAREHOUSE/

DATA LAKE

LEGACY RDBMS

HDFS BASED

BUSINESS

TRANSACTIONS

Web views

( Payments )

( Mobile Queries )

( Recommendation )

( And More )

High Performance NoSQL

“REAL-TIME BIG DATA”

“DECISIONING”

500Business Trans per sec

5000 Calculations per sec

X = 2.5 M Database Transactions per sec

Operational Scale


CREDIT CARD

PROCESSING SYSTEM

FRAUD DETECTION &

PROTECTION APP

ACCOUNT

BEHAVIOR

ACCOUNT

STATISTICS

STATIC DATA

RULE 1 – PASSED ✔

RULE 2 – PASSED ✔

RULE 3 – FAILED ✗

HISTORICAL

DATA

RULES

RULE 1

RULE 2

RULE 3

…

• Challenge

– Implement new algorithmsas new patterns develop

– Every transaction requires hundreds of DB reads/writes

– High, constant ingest rates

– Scale-up as algorithms and business grow

– Overall SLA 750 ms

• Need to scale reliably

– 10 100 TB

– 10B 100 B objects

– 200k I Million+ TPS

• Selected NoSQL

– Built for Flash

– Predictable Low latency at High Throughput

– Immediate consistency

– Cross data center (XDR) for high availability

Fraud Prevention


■ Challenge

■ DB2 stores positions for 10 Million customers

■ Value-at-risk calculations in minutes, not hours

■ Consistent view of trade state across all applications

■ Must update stock prices, show balances on 300

positions, process 250M transactions, 2 M updates/day

■ Cache uneconomical – 150 servers growing to 1000

■ Need to scale reliably

■ 3 13 TB

■ 100 400 Million objects

■ 200k I Million TPS

■ Selected NoSQL

■ Flash

■ Predictable Low latency at High Throughput

■ Immediate consistency

■ Cross data center (XDR) support

■ 10 Server Cluster

IBM DB2(MAINFRAME)

Read/Write

Start of Day

Data Loading

End of Day

Reconciliation

QueryREAL-TIME

DATA FEED

ACCOUNT

POSITIONS

XDR

Fin Serv – Positions System of Record


Challenge• Per-account routing rules win edge systems

• Traffic shaping to implement account policies

• 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 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

Telco – Real-Time Billing and Charging Systems


Challenge• Billions of users & cookies across the internet

• Accessible using provisioning applications

(self-serve and through support personnel)

• Real-time algorithms used for targeting, offers.

Need for Extremely High Availability,

Reliably, Low latency• 10’s TBs of data

• 1B ~ 10B objects

• 1M ~ 10M TPS

Selected NoSQL• Clustered HA system

• Predictable low latency at high throughput

• Highly-available and reliable on failure

• Cross data center (XDR) support

AdTech – Targeting, Bidding, Programmatic

INTERNET

AD EXCHANGE

BIDDING

APPLICATION

SEARCHES

VISITS

TIME ON PAGE

AUDIENCE

HISTORICAL

DATA

BEHAVIOR

MODELS

MACHINE

LEARNING


Aerospike – Enabling Your Digital Transformation

Powered by High

Performance NoSQL

Aerospike – The Next Generation

Operational Database

NEXT GENERATION ARCHITECTURE

• No cache required – simpler architecture

• Patented and Designed for Flash– Log structured File System

• Record Oriented, Schema Free NoSQL KV Store

PREDICTABLE PERFORMANCE

• DRAM or Hybrid DRAM/Flash for Persistence

• Stable, Low Latency and high throughput under any condition

• Deployable on Bare Metal, virtualized, containerized, or Cloud

DYNAMIC CLUSTERING

• Highest Uptime & Availability of any NoSQL (5 nines plus)

• Automatic DB Cluster formation, healing and dynamic sharding

• Master based synchronous replication – immediate consistency

• Cross Data Center Replication (XDR)

SMART APPS

• Machine Learning, Spark & Hadoop Integration

• Broad language support (C/C++, Java, C#, Python, Go, Node.js, PHP)

• Accelerated development – schema free

• Rich APIs, Geospatial and Secondary Indexes

TCO

• Optimized for Flash and DRAM

• Demonstrated 10:1 price performance savings

• Full Utilization ->10x reduction in servers deployed

• Huge operational efficiency – “Set it and Forget it”

$


Aerospike

Technology


Architecture

1) No Hotspots

– Distributed Hash Table simplifies data partitioning

2) Smart Client – 1 hop to data, no load balancers

3) Shared Nothing Architecture,

– every node is identical

4) Smart Cluster, Zero Touch

– auto-failover, rebalancing, rack aware, rolling upgrades

5) Transactions and long-running tasks prioritized in real-time

6) XDR – sync replication across data centers ensures

– Zero Downtime


OTHER DATABASE

OS FILE SYSTEM

PAGE CACHE

BLOCK INTERFACE

SSD HDD

BLOCK INTERFACE

SSD SSD

OPEN NVM

SSD

OTHER

DATABASE

AEROSPIKE FLASH OPTIMIZED

DATABASE

AEROSPIKE

HYBRID MEMORY SYSTEM™

• Direct device access

• Large Block Writes

• Indexes in DRAM

• Highly Parallelized

• Log-structured FS “copy-on-write”

• Fast restart with shared memory

Flash Optimized High Performance


2014: 1 M TPS on Single Server


Thank You

Questions?