Choosing a Next Gen Database: the New World Order of NoSQL, NewSQL, and MySQL

© 2012 by The 451 Group. All rights reserved

Choosing a Next-Gen Database The New World Order of NoSQL, NewSQL and MySQL

Matthew Aslett, 451 Research

Doron Levari & Paul Campaniello, ScaleBase


Agenda

1. 451 Research – Choosing a next-gen database 2. The New World Order of NoSQL, NewSQL and MySQL

3. ScaleBase - How to Scale Out your existing MySQL DB

4. Customer ROI/Case Studies

5. Q & A

(please type questions directly into the GoToWebinar side panel)


The 451 Group


451 Research

Information Management Operational databases

Data warehousing Data caching

Event processing

Matthew Aslett

• Research manager, data management and analytics

• With The 451 Group since 2007

• www.twitter.com/maslett

Commercial Adoption of Open Source (CAOS) Open source projects

Adoption of open source software Vendor strategies


In a nutshell

The database landscape has changed massively in the last 5 years

Database users – particularly MySQL users – have never had so much choice

And they are more prepared than ever to look at alternatives to the traditional incumbents

We have moved into an era of polyglot persistence

(and polyglot analytics)

Choosing the right database for the right workload is critical

And the choice ever been so confusing…

© 2012 by 451 Research. All rights reserved © 2012 by The 451 Group. All rights reserved

Relational

Non-relational Analytic

Oracle

Operational

IBM DB2

SQL Server PostgreSQL MySQL

Ingres SAP Sybase ASE

Teradata

Netezza

Greenplum

ParAccel

Vertica Calpont

Objectivity

MarkLogic

InterSystems

Versant

Progress

McObject

EnterpriseDB

SAP Sybase IQ

IBM InfoSphere

Aster

Infobright

Lotus Notes

The database landscape – 5ish years ago


Relational

Non-relational Analytic

Oracle

Operational

IBM DB2


SAP Sybase ASE

Teradata

IBM Netezza

EMC Greenplum

ParAccel

HP Vertica Calpont

Objectivity

MarkLogic

InterSystems

Versant

Progress

McObject

EnterpriseDB

SAP Sybase IQ

IBM InfoSphere Infobright

Lotus Notes

The database landscape – less than 5 years ago

Actian Ingres

Hadoop

Actian VectorWise Piccolo

Percona

SkySQL MariaDB

Teradata Aster

HPCC

SAP HANA


Relational Non-relational Analytic

Oracle

Operational

IBM DB2


Actian Ingres

SAP Sybase ASE

Hadoop

Teradata

Netezza

EMC Greenplum

ParAccel

HP Vertica Calpont

Lotus Notes

Objectivity

MarkLogic

InterSystems

Versant

Progress

McObject

EnterpriseDB

SAP Sybase IQ

IBM InfoSphere Actian VectorWise

Piccolo Infobright

Percona

SkySQL

MariaDB

Teradata Aster

HPCC

SAP HANA



Oracle

Operational

IBM DB2


Actian Ingres

SAP Sybase ASE

Teradata

Netezza

EMC Greenplum

ParAccel

HP Vertica Calpont

NoSQL

Document Lotus Notes

CouchDB MongoDB Key value

Big tables

Objectivity

MarkLogic

InterSystems

Versant

Progress

McObject

HBase Hypertable

Riak

Neo4J

EnterpriseDB

SAP Sybase IQ


Cassandra

Couchbase

Oracle NoSQL

Redis

Voldemort

Membrain

RavenDB

Citrusleaf

BerkeleyDB

Starcounter

Infobright

DEX

DynamoDB Iris Mongo Mongo Couch Lab HQ

Cloudant

Redis-to-go

Castle

Percona

SkySQL

MariaDB

RethinkDB

OrientDB

App Engine Datastore

InfiniteGraph

SimpleDB -as-a-Service

Graph

DataStax Enterprise

HandlerSocket*

LevelDB

NuvolaBase

Acunu

Hadoop

Piccolo

Teradata Aster

HPCC

SAP HANA



Oracle

Operational

IBM DB2


Actian Ingres

SAP Sybase ASE

Teradata

Netezza

EMC Greenplum

ParAccel

HP Vertica Calpont

NoSQL

Document Lotus Notes


Big tables

Objectivity

MarkLogic

InterSystems

Versant

Progress

McObject

HBase Hypertable

Riak

Neo4J

EnterpriseDB

SAP Sybase IQ


Cassandra

Couchbase

Oracle NoSQL

Redis

Voldemort

Membrain

RavenDB

Citrusleaf

BerkeleyDB

Starcounter

Teradata Aster

Infobright

DEX

NewSQL

VoltDB

ScaleArc Tokutek Continuent

Translattice

Database.com

NuoDB

Drizzle

ClearDB

Google Cloud SQL Rackspace MySQL Cloud

Storage engines

Postgres Plus Cloud

Clustering/sharding

New databases JustOneDB SQLFire

GenieDB

Akiban

ScaleDB

SchoonerSQL

MySQL Cluster Galera


Cloudant

Redis-to-go

Amazon RDS

SQL Azure

CodeFutures

ScaleBase

Zimory Scale

Clustrix

Castle

Percona

SkySQL

MariaDB

RethinkDB

ParElastic

OrientDB


InfiniteGraph

SimpleDB

-as-a-Service

Xeround

-as-a-Service

-as-a-Service

Graph

DataStax Enterprise

FathomDB

HandlerSocket*

LevelDB

NuvolaBase

Acunu

MemSQL

Piccolo

Hadoop

HPCC

SAP HANA

StormDB


NoSQL, NewSQL and Beyond

NoSQL

New breed of non-relational database products

Rejection of fixed table schema and join operations

Designed to meet scalability requirements of distributed architectures

And/or schema-less data management requirements



NoSQL





NewSQL

New breed of relational database products

Retain SQL and ACID


Or improve performance so horizontal scalability is no longer a necessity


Relevant reports


• Assessing the drivers behind the development and adoption of NoSQL and NewSQL databases, as well as data grid/caching technologies

• Released April 2011

• Role of open source in driving innovation

• [email protected]



NoSQL





NewSQL

New breed of relational database products

Retain SQL and ACID


Or improve performance so horizontal scalability is no longer a necessity

MySQL in the headlights

MySQL was once the default database for new Web applications. Now it faces a competitive challenge from alternative databases


SPRAINED RELATIONAL DATABASES

Photo credit: Foxtongue on Flickr http://www.flickr.com/photos/foxtongue/4844016087/


SPRAIN

The traditional relational database has been stretched beyond its normal capacity by the needs of high-volume, highly distributed or highly complex applications.

There are workarounds – such as DIY sharding – but manual,

homegrown efforts can result in database administrators being stretched beyond their normal capacity in terms of managing complexity.

Scalability Performance Relaxed consistency Increased willingness to look towards Agility emerging alternatives Intricacy Necessity


Alternatives

NoSQL

• *IF* suitable for the application and workload in terms of consistency, data model, and developer skillset

NoSQL

Document


Big tables HBase

Hypertable

Riak

Neo4J

Cassandra

Couchbase

Oracle NoSQL

Redis

Voldemort

Membrain

RavenDB

Citrusleaf

BerkeleyDB

DEX


Cloudant

Redis-to-go

Castle

RethinkDB

OrientDB


InfiniteGraph

SimpleDB -as-a-Service

Graph

DataStax Enterprise

HandlerSocket*

LevelDB

NuvolaBase

Acunu


Alternatives

NewSQL

• New databases

• Advanced storage engines, particularly for MySQL

• Advanced clustering/shard management approaches

• ParElastic • Continuent • Galera

• NuoDB • SQLFire

• Translattice • Clustrix

• SchoonerSQL • ScaleBase

• ScaleArc • CodeFutures

• GenieDB

• ScaleDB • MySQL Cluster • Zimory Scale

New databases

• StormDB • Xeround • Tokutek

Storage engines

• MemSQL • Drizzle • VoltDB • JustOneDB

Advanced clustering/sharding

-as-a-Service

• Datomic • Akiban


NewSQL approaches

New databases • Pros: Designed specifically to support distributed architecture • Cons: May lack compatibility with existing applications

Advanced storage engines, particularly for MySQL

• Pros: Retain familiarity with with MySQL skills, tools • Cons: Re-architecting from the inside out.

Advanced clustering/shard management approaches

• Pros: Retain application compatibility while adding scalability • Cons: An extra layer of complexity?

Issues to consider: • Does it require a forklift move of your entire application ecosystem • Can you continue to leverage your existing MySQL skill set? • Is there a risk for your data, e.g. memory reliability?


Spotlight on ScaleBase

Creates a shared nothing architecture from standard databases

Elastic load balancing for MySQL (other databases on the roadmap)

Scale Out via read/write splitting or automatic data distribution

Data Traffic Manager serves as a proxy between the apps and DB

Provides a single point for administering the shared nothing cluster (for performance, HA, change management)

And the ability to add scalability without the need to migrate to a new database architecture or make any changes to existing apps.


NewSQL and MySQL

Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem


• NuoDB • SQLFire

• Translattice • Clustrix

• SchoonerSQL • ScaleBase

• ScaleArc • CodeFutures

• GenieDB


New databases

• StormDB • Xeround • Tokutek

Storage engines

• MemSQL • Drizzle • VoltDB • JustOneDB


-as-a-Service

• Datomic • Akiban


NewSQL and MySQL

Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem


• Clustrix • SchoonerSQL

• ScaleBase • ScaleArc

• CodeFutures

• GenieDB


New databases

• Xeround • Tokutek

Storage engines

• Drizzle


-as-a-Service


Relevant reports

MySQL vs NoSQL and NewSQL: 2011-2015 Assessing the competitive

dynamic

Released May 2012 Including market sizing estimates

for all three sectors

Survey of 200+ database users [email protected]

https://451research.com/report-long?icid=2289 http://blogs.the451group.com/information_management/?p=1740


Conclusions

NoSQL and NewSQL pose a long-term threat to MySQL’s position as the default database for Web applications, given their use for new development projects.

NewSQL technologies are, at this stage, largely being adopted to improve the performance and scalability of existing databases, particularly MySQL.

The MySQL ecosystem is arguably more healthy and vibrant than ever, while, the options for MySQL users have never been greater.

And there is a significant portion of the MySQL user base that is willing to consider alternatives.

Choosing a Next-Gen Database How to Scale Out your MySQL Database

October 23, 2012

26

Who We Are

Presenters: Paul Campaniello,

VP of Global Marketing 25 year technology veteran with marketing experience at Mendix, Lumigent, Savantis and Precise.

Doron Levari, Founder A technologist and long-time

veteran of the database industry. Prior to founding ScaleBase, Doron

was CEO to Aluna.

27

Pain Points – The Scalability Problem

• Thousands of new online and mobile

apps launching every day

• Demand climbs for these apps and

databases can’t keep up

• App must provide uninterrupted

access and availability

• Database performance and

scalability is critical

28

Big Data = Big Scaling Needs

The 451 Group & Teradata

Big Data = Transactions + Interactions + Observations

BIG

DA

TA

ER

P

CR

M

WE

B

Petabytes

Terabytes

Gigabytes

Megabytes

Increasing Data Variety and Complexity

Purchase Detail

Purchase Record

Payment Record

Segmentation

Offer Details

Customer Touches

Support Contacts

Web Logs

Offer History A/B Testing

Dynamic Pricing

Affiliate Networks

Search Marketing

Behavioral

Targeting

Dynamic

Funnels

Sensors/RFID/Devices

User Click Stream

Mobile Web

Sentiment

User Generated Content

Social Interactions & Feeds

Spatial & GPS Coordinates

External

Demographics

Business Data

Feeds

HD Video, Audio, Images

Speech to Text

Product/Service Logs

SMS/MMS

29

SPRAIN

• The traditional relational database has been stretched beyond its normal capacity by the needs of high-volume, highly distributed or highly complex applications.

• There are workarounds – such as sharding – but manual, homegrown efforts can result in database administrators being stretched beyond their normal capacity in terms of managing complexity.

– Scalability

– Performance

– Relaxed consistency Increased willingness to look towards

– Agility emerging scale out alternatives

– Intricacy

– Necessity

30

The Real $prain Pain

You just lost

customers

Infrastructure Cost $

time

Large

Capital

Expenditure

Opportunity

Cost

Predicted Demand

Traditional Hardware

Actual Demand

Dynamic Scaling

31

Fix the $prain Pain: Scale-Out Your MySQL

• Keep your MySQL - keep your InnoDB

• Ecosystem compatibility, preserve skills

• 100% Application compatibility

– MySQL is the starting point...

it can only get better from there…

• Your data is safe!

• Smoother, no down-time, no forklift

• No “in-memory” magic

• No “in-memory” size limit

Don’t throw out the baby with the bath water!

32

Scale Out (two methods)

Write

Read

Replication

Read/Write Splitting

Automatic Data Distribution

1

2

33

Scale Out via Read/Write Splitting

• Excellent solution for scaling high session-volume reads

• Helps with writes too as master is freed up!

• With ScaleBase:

– Ensure data consistency with replication monitoring and lag-based load-

balancing

– Transaction aware, improved data consistency and isolation thru master

stickiness

– Simplify management, reduce TCO with real-time monitoring and alerts

34

Scale Out via Automatic Data Distribution

• The ultimate way to scale

• Delivers significant performance improvements

• Good for scaling high data-volume and session-volume reads and writes

• With ScaleBase:

– Best data-distribution policy to optimize database utilization

– Guarantee system-wide data consistency

– Improved performance with parallel query execution

– No downtime

– Reconstruct query results in real time

– Maintain unified view, support for ORDER BY, GROUP BY, LIMIT, Aggregate functions…

– Simplify management, reduce TCO with real-time monitoring and alerts

35

Scale Out Provides Immediate & Tangible Value

Application Server

BI

Management

Application Server

Database A Standby A

Database B Standby B

Database C Standby C

Database D Standby D

36

Choose Your Scale-out Path

# of concurrent sessions

Dat

abas

e S

ize

1 DB?

Good for me!

Data Distribution (Reads and writes)

Read/Write Splitting (Reads)

37

Detailed Scale Out Case Studies

Nokia

• Device Apps App

• Availability

• Scalability

• Geo-clustering

• 100 Apps

• 300 MySQL DB

Solar Edge

• Next Gen Monitoring App

• Massive Scale

• Monitors real time data from thousands of distributed systems

Mozilla

• New Product/ Next Gen App/ AppStore

• Scalability

• Geo-sharding

AppDynamics

• Next gen APM company

• Scalability for the Netflix implementation

38

Summary

• Database scalability is a significant problem (SPRAIN)

– App explosion, Big Data and mobile compound it

• The MySQL ecosystem is more healthy and vibrant than ever

• ScaleBase provides long term, cost-effective Scale Out solutions

(R/W splitting & data distribution)

– No ecosystem forklift

– 100% application compatibility

(i.e. no app rewrites)

– Leverage your existing MySQL skill set

– Data is never at risk

39

Questions (please enter directly into the GTW side panel)

[email protected]

[email protected]

@scalebase

www.ScaleBase.com

617.630.2800

[email protected]

@maslett

@451research

www.451research.com

http://www.scalebase.com/

http://www.451research.com/

40

Thank You

Documents

Choosing a Next Gen Database: the New World Order of NoSQL, NewSQL, and MySQL