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DISTRIBUTED CACHES & STORAGES
INTRODUCTION & CLASSIFICATION
                         Max Alexejev
                          11/07/2012
        Moscow Big Systems/Big Data
About me
• 10 years experience in Java development
• Recently – In-Memory Data Grids consultant on
  various projects in Silicon Valley, USA
• Now – Tech Lead at one of invested startups in
  Moscow
• Specialized in distributed systems design, Java
  performance and GC tuning, caching and data grids

Friend of LifeStreet Media 
Lots of products in the wild
 Memcached                          Cassandra
                                                        GemStone
                  Hazelcast
                                                         GemFire

      Riak                                    Redis                 HBase
                         Oracle
                       Coherence
                                                      Infinispan
      Voldemort                     Tokyo
                                   Kabinet                         CouchDB
             MongoDB
                                    EhCache
  Neo4j                                                      …
How to classify?
   Type
   Origin
   CAP relation
By Type

                                                                                          Legacy and
    RDBMS            Key Value     NoSQL                        IMDG                GIS
                                                                                            Exotics




No, not this time   Memcached,   Explanation   Computational-
                                                                        Generic
                    EhCache      follows…        or Data-




                                                                       Coherence,
                                                                       GemFire,
                                                                       GridGain …
NoSQL – so, “Not Only” or “Not”?
                                       NoSQL




  Column-based:                                 KV+
                  Document-oriented:
     HBase,                                     Riak,
                      CouchDB,                                            Graph
   Cassandra,                                  Redis,
                      MongoDB
    SimpleDB                                   LevelDB




                                                         Full-featured:           Simplified:
                                                            Neo4J                  FlockDB
Origins: The famous PDFs
  Amazon Dynamo Paper

  • allthingsdistributed.com/files/amazon-dynamo-sosp2007.pdf

  Google BigTable Paper

  • research.google.com/archive/bigtable-osdi06.pdf

  Zookeeper distributed protocol

  • research.yahoo.com/files/ladis08.pdf (Zab protocol)
CAP properties breakdown
      CP-class:                                            CA-class:
All BigTable-based           Consistency                   RDBMS,
     (BigTable,                                             IMDG
HyperTable, Hbase,
      LevelDB)
 MongoDB, Redis,
  MemcacheDb          Partition
                                      Availability
                     Tolerance



                                AP-class:
               All Dynamo-based (DynamoDB, Cassandra,
              Voldemort, Riak), CouchDB, SimpleDB, Tokyo
                   Kabinet, Odnoklassniki’s distr. cache
Let’s use it right now for our
brand-new startup!!!

   ACID guarantees & Transactions?
   Data distribution & replication?
   Durability support?
   Ad-hoc queries?
   Operations-friendly?
   Active community?
   Additional risk management involved.
QUESTIONS?

AND CONTACTS
   HTTP://MAKSIMALEKSEEV.MOIKRUG.RU/
   HTTP://RU.LINKEDIN.COM/PUB/MAX-ALEXEJEV/51/820/AB9
   MALEXEJEV@GMAIL.COM
   SKYPE: MALEXEJEV

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Distributed Caches and Storages - presentation

  • 1. DISTRIBUTED CACHES & STORAGES INTRODUCTION & CLASSIFICATION Max Alexejev 11/07/2012 Moscow Big Systems/Big Data
  • 2. About me • 10 years experience in Java development • Recently – In-Memory Data Grids consultant on various projects in Silicon Valley, USA • Now – Tech Lead at one of invested startups in Moscow • Specialized in distributed systems design, Java performance and GC tuning, caching and data grids Friend of LifeStreet Media 
  • 3. Lots of products in the wild Memcached Cassandra GemStone Hazelcast GemFire Riak Redis HBase Oracle Coherence Infinispan Voldemort Tokyo Kabinet CouchDB MongoDB EhCache Neo4j …
  • 4. How to classify?  Type  Origin  CAP relation
  • 5. By Type Legacy and RDBMS Key Value NoSQL IMDG GIS Exotics No, not this time Memcached, Explanation Computational- Generic  EhCache follows… or Data- Coherence, GemFire, GridGain …
  • 6. NoSQL – so, “Not Only” or “Not”? NoSQL Column-based: KV+ Document-oriented: HBase, Riak, CouchDB, Graph Cassandra, Redis, MongoDB SimpleDB LevelDB Full-featured: Simplified: Neo4J FlockDB
  • 7. Origins: The famous PDFs Amazon Dynamo Paper • allthingsdistributed.com/files/amazon-dynamo-sosp2007.pdf Google BigTable Paper • research.google.com/archive/bigtable-osdi06.pdf Zookeeper distributed protocol • research.yahoo.com/files/ladis08.pdf (Zab protocol)
  • 8. CAP properties breakdown CP-class: CA-class: All BigTable-based Consistency RDBMS, (BigTable, IMDG HyperTable, Hbase, LevelDB) MongoDB, Redis, MemcacheDb Partition Availability Tolerance AP-class: All Dynamo-based (DynamoDB, Cassandra, Voldemort, Riak), CouchDB, SimpleDB, Tokyo Kabinet, Odnoklassniki’s distr. cache
  • 9. Let’s use it right now for our brand-new startup!!!  ACID guarantees & Transactions?  Data distribution & replication?  Durability support?  Ad-hoc queries?  Operations-friendly?  Active community?  Additional risk management involved.
  • 10. QUESTIONS? AND CONTACTS  HTTP://MAKSIMALEKSEEV.MOIKRUG.RU/  HTTP://RU.LINKEDIN.COM/PUB/MAX-ALEXEJEV/51/820/AB9  MALEXEJEV@GMAIL.COM  SKYPE: MALEXEJEV

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