Choosing a Next-Gen DatabaseThe New World Order of NoSQL, NewSQL and MySQLMatthew Aslett, 451 Research                    ...
Agenda  1. 451 Research – Choosing a next-gen database  2. The New World Order of NoSQL, NewSQL and MySQL  3. ScaleBase - ...
The 451 Group                © 2012 by The 451 Group. All rights reserved
451 Research Matthew Aslett  • Research manager, data management and analytics  • With The 451 Group since 2007  • www.tw...
In a nutshell The database landscape has changed massively in the last 5 years Database users – particularly MySQL users...
The database landscape – 5ish years ago                                                                           Relation...
The database landscape – less than 5 years ago                                                                           R...
Non-relational                                                 Relational                     Analytic     Hadoop Teradata...
Non-relational                                                             Relational                                Analy...
Non-relational                                                            Relational                               Analyti...
NoSQL, NewSQL and Beyond NoSQL  New breed of non-relational   database products  Rejection of fixed table   schema and j...
NoSQL, NewSQL and Beyond NoSQL                                               NewSQL  New breed of non-relational         ...
Relevant reports NoSQL, NewSQL and Beyond  • Assessing the drivers behind the development and adoption    of NoSQL and Ne...
NoSQL, NewSQL and Beyond NoSQL                                               NewSQL  New breed of non-relational         ...
SPRAINED RELATIONAL DATABASESPhoto 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, ...
Alternatives NoSQL  • *IF* suitable for the application and workload in terms of consistency,    data model, and develope...
Alternatives NewSQL  • New databases  • Advanced storage engines, particularly for MySQL  • Advanced clustering/shard man...
NewSQL approaches New databases  • Pros: Designed specifically to support distributed architecture  • Cons: May lack comp...
Spotlight on ScaleBase Creates a shared nothing architecture from standard databases Elastic load balancing for MySQL (o...
NewSQL and MySQL Many NewSQL offerings are designed to complement MySQL, and  can also be considered part of the MySQL ec...
NewSQL and MySQL Many NewSQL offerings are designed to complement MySQL, and  can also be considered part of the MySQL ec...
Relevant reportsMySQL vs NoSQL and NewSQL: 2011-2015 Assessing the competitive  dynamic Released May 2012 Including mar...
Conclusions NoSQL and NewSQL pose a long-term threat to MySQL’s position asthe default database for Web applications, giv...
Choosing a Next-Gen DatabaseHow to Scale Out your MySQL Database                                  October 23, 2012
Who We Are Presenters:                                     Paul Campaniello,                                              ...
Pain Points – The Scalability Problem• Thousands of new online and mobile  apps launching every day• Demand climbs for the...
Big Data = Big Scaling Needs    Big Data = Transactions + Interactions + Observations            Sensors/RFID/Devices     ...
SPRAIN • The traditional relational database has been stretched beyond   its normal capacity by the needs of high-volume, ...
The Real $prain PainInfrastructureCost $                   Large                     You just lost                   Capit...
Fix the $prain Pain: Scale-Out Your MySQL Don’t throw out the baby with the bath water! • Keep your MySQL - keep your Inno...
Scale Out (two methods)                                             Read                                             Write...
Scale Out via Read/Write Splitting • Excellent solution for scaling high session-volume reads • Helps with writes too as m...
Scale Out via Automatic Data Distribution •   The ultimate way to scale •   Delivers significant performance improvements ...
Scale Out Provides Immediate & Tangible Value     Application Server            Database A    Standby A     Application Se...
Choose Your Scale-out Path                              Data Distribution                              (Reads and writes) ...
Detailed Scale Out Case Studies     Nokia               AppDynamics             Mozilla           Solar Edge     • Device ...
Summary     • Database scalability is a significant problem (SPRAIN)        – App explosion, Big Data and mobile compound ...
Questions (please enter directly into the GTW side panel)matt.aslett@451research.com         paul.campaniello@scalebase.co...
Thank You40
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Choosing a Next Gen Database: the New World Order of NoSQL, NewSQL, and MySQL

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In this webinar Matt Aslett of 451 Research joins ScaleBase to discuss the benefits and drawbacks of NoSQL, NewSQL & MySQL databases and explores real-life use cases for each.

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

  1. 1. Choosing a Next-Gen DatabaseThe New World Order of NoSQL, NewSQL and MySQLMatthew Aslett, 451 Research Doron Levari & Paul Campaniello, ScaleBase © 2012 by The 451 Group. All rights reserved
  2. 2. 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
  3. 3. The 451 Group © 2012 by The 451 Group. All rights reserved
  4. 4. 451 Research Matthew Aslett • Research manager, data management and analytics • With The 451 Group since 2007 • www.twitter.com/maslettInformation Management Commercial Adoption of Open Source Operational databases (CAOS) Data warehousing  Open source projects Data caching  Adoption of open source software Event processing  Vendor strategies © 2012 by The 451 Group. All rights reserved
  5. 5. 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 The 451 Group. All rights reserved
  6. 6. The database landscape – 5ish years ago Relational Non-relational Analytic Aster Netezza ParAccel SAP Sybase IQ Infobright Greenplum IBM InfoSphere Teradata Calpont VerticaMarkLogic Oracle IBM DB2Versant MySQL PostgreSQL SQL ServerMcObject SAP Sybase ASE IngresProgress Lotus NotesObjectivity InterSystems EnterpriseDBOperational © 2012 by 451 Research. AllAll rights reserved © 2012 by The 451 Group. rights reserved
  7. 7. The database landscape – less than 5 years ago Relational Non-relational Analytic Hadoop Teradata Aster IBM Netezza ParAccel SAP Sybase IQ Piccolo Infobright EMC Greenplum IBM InfoSphere HPCC Teradata Calpont Actian VectorWise HP VerticaMarkLogic Oracle SAP HANA Percona IBM DB2 MariaDBVersant SkySQL MySQL PostgreSQL SQL ServerMcObject SAP Sybase ASE Actian IngresProgress Lotus NotesObjectivity InterSystems EnterpriseDBOperational © 2012 by 451 Research. AllAll rights reserved © 2012 by The 451 Group. rights reserved
  8. 8. Non-relational Relational Analytic Hadoop Teradata Aster Netezza ParAccel SAP Sybase IQ Piccolo Infobright EMC Greenplum IBM InfoSphere HPCC Teradata Calpont Actian VectorWise HP Vertica SAP HANA Oracle Percona IBM DB2 MariaDBMarkLogic SkySQL MySQL PostgreSQL SQL ServerVersant Actian Ingres EnterpriseDB SAP Sybase ASEMcObjectProgressObjectivity Lotus Notes Operational InterSystems © 2012 by 451 Research. AllAll rights reserved © 2012 by The 451 Group. rights reserved
  9. 9. Non-relational Relational Analytic Hadoop Teradata Aster Netezza ParAccel SAP Sybase IQ Piccolo Infobright EMC Greenplum IBM InfoSphere HPCC Teradata Calpont Actian VectorWise HP Vertica NoSQL SAP HANA DataStax Enterprise Oracle Percona IBM DB2 MariaDBMarkLogic Castle Acunu Neo4J SkySQL MySQL PostgreSQL SQL Server Citrusleaf Graph HypertableVersant BerkeleyDB Cassandra HBase InfiniteGraph Actian Ingres OrientDB Oracle NoSQL Big tables EnterpriseDB RethinkDB App Engine DEX HandlerSocket* Datastore NuvolaBase SAP Sybase ASEMcObject Riak Redis-to-go -as-a-Service SimpleDB LevelDB DynamoDBProgress Redis Iris Mongo Mongo Cloudant Membrain Couch Lab HQ Voldemort RavenDB Couchbase Key value MongoDB CouchDBObjectivity Lotus Notes Document Operational Starcounter InterSystems © 2012 by 451 Research. AllAll rights reserved © 2012 by The 451 Group. rights reserved
  10. 10. Non-relational Relational Analytic Hadoop Teradata Aster Netezza ParAccel SAP Sybase IQ Piccolo Infobright EMC Greenplum IBM InfoSphere HPCC Teradata Calpont Actian VectorWise HP Vertica NoSQL SAP HANA DataStax Enterprise Oracle Percona IBM DB2 MariaDBMarkLogic Castle Acunu Neo4J SkySQL MySQL PostgreSQL SQL Server Citrusleaf Graph HypertableVersant BerkeleyDB Cassandra HBase InfiniteGraph -as-a-Service FathomDB Actian Ingres OrientDB Amazon RDS Database.com Oracle NoSQL Big tables Postgres Plus Cloud ClearDB EnterpriseDB RethinkDB App Engine DEX Rackspace MySQL Cloud HandlerSocket* Datastore NuvolaBase SAP Sybase ASE Google Cloud SQL SQL AzureMcObject Riak Redis-to-go -as-a-Service SimpleDB NewSQL LevelDB DynamoDBProgress Redis NuoDB VoltDB New databases Membrain Iris Mongo Mongo Cloudant -as-a-Service MemSQL JustOneDB SQLFire Couch Lab HQ StormDB Drizzle Akiban Translattice Voldemort RavenDB Couchbase Xeround SchoonerSQL Clustrix GenieDB Key value MongoDB CouchDB ScaleArc ParElastic Tokutek ScaleDB Zimory Scale ContinuentObjectivity Storage MySQL Cluster Galera CodeFutures Lotus Notes Document engines ScaleBase Clustering/sharding Operational Starcounter InterSystems © 2012 by 451 Research. AllAll rights reserved © 2012 by The 451 Group. rights reserved
  11. 11. 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
  12. 12. NoSQL, NewSQL and Beyond NoSQL NewSQL  New breed of non-relational  New breed of relational database products database products  Rejection of fixed table  Retain SQL and ACID schema and join operations  Designed to meet scalability  Designed to meet scalability requirements of distributed requirements of distributed architectures architectures  Or improve performance so  And/or schema-less data horizontal scalability is no management requirements longer a necessity © 2012 by The 451 Group. All rights reserved
  13. 13. 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
  14. 14. NoSQL, NewSQL and Beyond NoSQL NewSQL  New breed of non-relational  New breed of relational database products database products  Rejection of fixed table  Retain SQL and ACID schema and join operations  Designed to meet scalability  Designed to meet scalability requirements of distributed requirements of distributed architectures architectures  Or improve performance so  And/or schema-less data horizontal scalability is no management requirements 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
  15. 15. SPRAINED RELATIONAL DATABASESPhoto credit: Foxtongue on Flickr http://www.flickr.com/photos/foxtongue/4844016087/ © 2012 by The 451 Group. All rights reserved
  16. 16. 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
  17. 17. Alternatives NoSQL • *IF* suitable for the application and workload in terms of consistency, data model, and developer skillset NoSQL DataStax Enterprise Castle Acunu Neo4J Citrusleaf Graph Hypertable BerkeleyDB Cassandra HBase InfiniteGraph OrientDB Oracle NoSQL Big tables RethinkDB App Engine DEX HandlerSocket* Datastore NuvolaBase Riak Redis-to-go -as-a-Service SimpleDB LevelDB DynamoDB Redis Iris Mongo Mongo Cloudant Membrain Couch Lab HQ Voldemort RavenDB Couchbase Key value MongoDB CouchDB Document © 2012 by The 451 Group. All rights reserved
  18. 18. Alternatives NewSQL • New databases • Advanced storage engines, particularly for MySQL • Advanced clustering/shard management approaches-as-a-Service • Datomic • MemSQL New databases• StormDB • Akiban • Drizzle • NuoDB• Xeround • VoltDB • SQLFire• Tokutek • JustOneDB • Translattice • GenieDB • Clustrix • SchoonerSQL • ScaleDB • ParElastic • ScaleBaseStorage engines • MySQL Cluster • Continuent • ScaleArc • Zimory Scale • Galera • CodeFutures Advanced clustering/sharding © 2012 by The 451 Group. All rights reserved
  19. 19. 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
  20. 20. 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 anew database architecture or make any changes to existing apps. © 2012 by The 451 Group. All rights reserved
  21. 21. NewSQL and MySQL Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem-as-a-Service • Datomic • MemSQL New databases• StormDB • Akiban • Drizzle • NuoDB• Xeround • VoltDB • SQLFire• Tokutek • JustOneDB • Translattice • GenieDB • Clustrix • SchoonerSQL • ScaleDB • ParElastic • ScaleBaseStorage engines • MySQL Cluster • Continuent • ScaleArc • Zimory Scale • Galera • CodeFutures Advanced clustering/sharding © 2012 by The 451 Group. All rights reserved
  22. 22. NewSQL and MySQL Many NewSQL offerings are designed to complement MySQL, and can also be considered part of the MySQL ecosystem-as-a-Service New databases • Drizzle• Xeround• Tokutek • GenieDB • Clustrix • SchoonerSQL • ScaleDB • ParElastic • ScaleBaseStorage engines • MySQL Cluster • Continuent • ScaleArc • Zimory Scale • Galera • CodeFutures Advanced clustering/sharding © 2012 by The 451 Group. All rights reserved
  23. 23. Relevant reportsMySQL 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
  24. 24. Conclusions NoSQL and NewSQL pose a long-term threat to MySQL’s position asthe default database for Web applications, given their use for newdevelopment projects. NewSQL technologies are, at this stage, largely being adopted toimprove the performance and scalability of existing databases,particularly MySQL. The MySQL ecosystem is arguably more healthy and vibrant thanever, while, the options for MySQL users have never been greater. And there is a significant portion of the MySQL user base that iswilling to consider alternatives. © 2012 by The 451 Group. All rights reserved
  25. 25. Choosing a Next-Gen DatabaseHow to Scale Out your MySQL Database October 23, 2012
  26. 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.26
  27. 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 critical27
  28. 28. Big Data = Big Scaling Needs Big Data = Transactions + Interactions + Observations Sensors/RFID/Devices Mobile Web User Generated Content Spatial & GPS Coordinates BIG DATAPetabytes User Click Stream Sentiment Social Interactions & Feeds Web Logs Dynamic Pricing Search Marketing WEB Offer History A/B Testing Affiliate NetworksTerabytes External Demographics Segmentation Customer Touches CRM Business Data Offer Details Support Contacts FeedsGigabytes HD Video, Audio, Images Behavioral ERP Purchase Detail Targeting Speech to Text Purchase Record Product/Service Logs Payment Record Dynamic Funnels SMS/MMSMegabytes Increasing Data Variety and Complexity 28 The 451 Group & Teradata
  29. 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 – Necessity29
  30. 30. The Real $prain PainInfrastructureCost $ Large You just lost Capital customers Expenditure Predicted Demand Opportunity Traditional Cost Hardware Actual Demand Dynamic Scaling time 30
  31. 31. Fix the $prain Pain: Scale-Out Your MySQL Don’t throw out the baby with the bath water! • 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 limit31
  32. 32. Scale Out (two methods) Read Write Read/Write1 Splitting Replication Automatic Data2 Distribution 32
  33. 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 alerts33
  34. 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 alerts34
  35. 35. Scale Out Provides Immediate & Tangible Value Application Server Database A Standby A Application Server Database B Standby B Database C Standby C BI Database D Standby D Management35
  36. 36. Choose Your Scale-out Path Data Distribution (Reads and writes) Database Size Read/Write Splitting (Reads) 1 DB? Good for me! # of concurrent sessions36
  37. 37. Detailed Scale Out Case Studies Nokia AppDynamics Mozilla Solar Edge • Device Apps App • Next gen APM • New Product/ • Next Gen • Availability company Next Gen App/ Monitoring App • Scalability • Scalability for the AppStore • Massive Scale • Geo-clustering Netflix • Scalability • Monitors real implementation • Geo-sharding time data from • 100 Apps thousands of • 300 MySQL DB distributed systems37
  38. 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 risk38
  39. 39. Questions (please enter directly into the GTW side panel)matt.aslett@451research.com paul.campaniello@scalebase.com doron.levari@scalebase.com @maslett @scalebase @451research www.ScaleBase.com www.451research.com 617.630.280039
  40. 40. Thank You40

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