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Data in the cloud O’Reilly MySQL Conference Mårten Mickos CEO, Eucalyptus Systems www.twitter.com/martenmickos

Data in the cloud O’Reilly MySQL Conference Mårten Mickos CEO, Eucalyptus Systems www.twitter.com/martenmickos. Infrastructure software. users. now. 10bn. 1bn. 100m. 10m. 1m. LAMP. MF. Mini. Client/Server. Cloud. Internet era. Web, Web2.0, Mobile internet. WANTED: MySQL

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Data in the cloud O’Reilly MySQL Conference Mårten Mickos CEO, Eucalyptus Systems www.twitter.com/martenmickos

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  1. Data in the cloudO’Reilly MySQL ConferenceMårten Mickos CEO, Eucalyptus Systemswww.twitter.com/martenmickos

  2. Infrastructure software users now 10bn 1bn 100m 10m 1m LAMP MF Mini Client/Server Cloud Internet era Web, Web2.0, Mobile internet

  3. WANTED: MySQL DEAD OR ALIVE

  4. WANTED: MySQL DEAD OR ALIVE & KICKING REWARD: $1,000,000,000

  5. FOSS model Ten years ago • disruptive movement lead by innovative growth companies • distribution-centric software model • enabled by the internet Today • an established practice lead by large corporations • service-centric software model • being redefined by cloud computing

  6. Dominant db designs big data scale-out RDBMS NoSQL / NewSQL land scale-up RDBMS key/ value ? doc db graph db 80s & 90s 00s & 10s 10s & 20s 0% 1% 10% 30% of world population online

  7. MySQL - NoSQL - NewSQL Akiban, Cassandra, Citrusleaf, Clustrix, Couchbase, Dynomite, FlockDB, GenieDB, Hadoop, Hive, HyperGraphDB, HyperTable, MarkLogic Server, Memcached, MemSQL, MongoDB, MySQL, MySQL Cluster, MySQL with HandlerSocket, Neo4J, NimbusDB, Objectivity/DB, Ravel, Redis, RethinkDB, Riak, SimpleDB, Terracotta, Tokyo Cabinet, Voldemort, VoltDB, Xeround

  8. Reversal of DBMS design principles Client/Server Cloud Strength Weakness Strength complex feature set scale-up ACID Weakness simplicity scale-out non-ACID

  9. Data in the cloud • Design the database for scale-out on multiple nodes • separate read activity from write activity • scale reads through replication • scale writes through sharding & partitioning • consider different dbms:s for different uses within the application • plan for failures • plan for 10x growth steps • Deploy on a cloud service (public) or cloud platform (private, on-prem) with common abstraction layer (API)

  10. Elastic scale-out in the clouds app app app app app app app Amazon Web Services (AWS) EC2, EBS, S3 Eucalyptus Cloud controller, storage controller, Walrus vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm vm

  11. Future • Cloud, Mobile & Social are the drivers, and they are bigger than anything we’ve seen • Existing models of FOSS, community and distribution being disrupted • Major rewards for creating the winning solution(s) for data in the cloud

  12. Thank you! Mårten Mickos marten@eucalyptus.com twitter.com/martenmickos

  13. Eucalyptus cloud platform Over 25,000 new Eucalyptus clouds were started in 2010

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