Post on 26-Jan-2015
description
© 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
© 2012 by The 451 Group. All rights reserved
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)
© 2012 by The 451 Group. All rights reserved
The 451 Group
© 2012 by The 451 Group. All rights reserved
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
© 2012 by The 451 Group. All rights reserved
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
© 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
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
© 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
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
© 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
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
IBM InfoSphere Actian VectorWise
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
© 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
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
IBM InfoSphere Actian VectorWise
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
DynamoDB Iris Mongo Mongo Couch Lab HQ
Cloudant
Redis-to-go
Amazon RDS
SQL Azure
CodeFutures
ScaleBase
Zimory Scale
Clustrix
Castle
Percona
SkySQL
MariaDB
RethinkDB
ParElastic
OrientDB
App Engine Datastore
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
© 2012 by The 451 Group. All rights reserved
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
© 2012 by The 451 Group. All rights reserved
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
NewSQL
New breed of relational database products
Retain SQL and ACID
Designed to meet scalability requirements of distributed architectures
Or improve performance so horizontal scalability is no longer a necessity
© 2012 by The 451 Group. All rights reserved
Relevant reports
NoSQL, NewSQL and Beyond
• 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
• sales@the451group.com
© 2012 by The 451 Group. All rights reserved
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
NewSQL
New breed of relational database products
Retain SQL and ACID
Designed to meet scalability requirements of distributed architectures
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
© 2012 by The 451 Group. All rights reserved
SPRAINED RELATIONAL DATABASES
Photo credit: Foxtongue on Flickr http://www.flickr.com/photos/foxtongue/4844016087/
© 2012 by The 451 Group. All rights reserved
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
© 2012 by The 451 Group. All rights reserved
Alternatives
NoSQL
• *IF* suitable for the application and workload in terms of consistency, data model, and developer skillset
NoSQL
Document
CouchDB MongoDB Key value
Big tables HBase
Hypertable
Riak
Neo4J
Cassandra
Couchbase
Oracle NoSQL
Redis
Voldemort
Membrain
RavenDB
Citrusleaf
BerkeleyDB
DEX
DynamoDB Iris Mongo Mongo Couch Lab HQ
Cloudant
Redis-to-go
Castle
RethinkDB
OrientDB
App Engine Datastore
InfiniteGraph
SimpleDB -as-a-Service
Graph
DataStax Enterprise
HandlerSocket*
LevelDB
NuvolaBase
Acunu
© 2012 by The 451 Group. All rights reserved
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
© 2012 by The 451 Group. All rights reserved
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?
© 2012 by The 451 Group. All rights reserved
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.
© 2012 by The 451 Group. All rights reserved
NewSQL and MySQL
Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem
• 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
© 2012 by The 451 Group. All rights reserved
NewSQL and MySQL
Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem
• ParElastic • Continuent • Galera
• Clustrix • SchoonerSQL
• ScaleBase • ScaleArc
• CodeFutures
• GenieDB
• ScaleDB • MySQL Cluster • Zimory Scale
New databases
• Xeround • Tokutek
Storage engines
• Drizzle
Advanced clustering/sharding
-as-a-Service
© 2012 by The 451 Group. All rights reserved
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 sales@the451group.com
https://451research.com/report-long?icid=2289 http://blogs.the451group.com/information_management/?p=1740
© 2012 by The 451 Group. All rights reserved
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)
paul.campaniello@scalebase.com
doron.levari@scalebase.com
@scalebase
www.ScaleBase.com
617.630.2800
matt.aslett@451research.com
@maslett
@451research
www.451research.com
40
Thank You