Breaking the Relational Headlock: A Survey of NoSQL Datastores

http://www.flickr.com/photos/fpat/3328595063/Gary Dusbabek

Full Disclosure:I work on Apache Cassandra. http://www.flickr.com/photos/vmanso/4040094281/

My Goals For You Should I? How Then? Achtung! http://www.flickr.com/photos/29707865@N05/2780508266/

http://www.flickr.com/photos/marc_smith/6246957472/A Brief History of Databases

http://www.flickr.com/photos/watchsmart/1422274819/

New StuffDirect access storageReplaced TapeNew Possibilities http://www.flickr.com/photos/byrion/5264950510/

Navigational Databases (two kinds)

Hierarchical Parent-child

NetworkRelationships Graph

Relational Model Search by content Good for query Demands on processor Rigid, fixed structures Bad for modelinghttp://www.flickr.com/photos/35536700@N07/3292544674

Data needs have changed http://www.flickr.com/photos/franzhaas/6761917637/

Technology has changedhttp://www.flickr.com/photos/neosnaps/2574417351/

http://www.flickr.com/photos/katclay/3935629242/ Choosing

ChoosingTechnology is Hard ™ Work .

Can you do it with arelational database?Is your DB falling apart? What do you need?

Where RDBMS Fall ApartScalingSPoFShardingDenormalizingAvailability Slave Systems http://www.flickr.com/photos/horiavarlan/4681206711/

What do you need? Reduced cost Throughput Availability Recoverability Correctness Transactionshttp://www.flickr.com/photos/ell-r-brown/5866777592/ Flexible Schema

What is NoSQL? Flighthttp://www.flickr.com/photos/24277960@N08/2609390563/http://www.flickr.com/photos/taylar/4996955547/http://www.flickr.com/photos/gromgull/611019520/http://www.flickr.com/photos/igboo/2583174998/

What isn’t NoSQL? NoFlighthttp://www.flickr.com/photos/alanvernon/3121751152/http://www.flickr.com/photos/tomsaint/3209482579/http://www.flickr.com/photos/pointnshoot/408384715/http://www.flickr.com/photos/zigazou76/5846255426/

Considerations Fault Tolerance Recovery Replication Access Hooks Distributed

Considerations Data Model Query/Search modelTransactional SemanticsRead vs Write ThroughputDeployment/Management

Focus on a few systems MongoDB Master-Slave RedisFullyDistributed Riak HBase Cassandra http://www.flickr.com/photos/seier/2455551478/sizes/l/in/photostream/

MongoDBDocument OrientedNaturally denormalizedFlexible schema

MongoDBProgrammer friendlyMany language driversAtomic on a single document

MongoDBReal-time datawarehousing/analyticsBlocking/offline compactionComplicated queries

MongoDBdb.foo.find({j: {$ne: 3}, k: {$gt: 10} });db.foo.find( { name : "bob" , $or : [ { a : 1 } , { b : 2 } ] } )

MongoDBMaster-slave replication AsynchronousGives failover & data redundancy But not consistency Only master can receive writesMakes atomic writes easy

Redis Real-time statstracking Wicked fast Collections built in

RedisIn-memorySnapshotsMaster-slaveRAM limited

RiakRelationships, aka “Links”Built-in MapReduceCompletely schemalessNo SPoFScales linearlyTunable consistency

RiakPre- Post-HooksConfigurable storage enginesREST accessEasy cluster balancing

RiakDoesn’t keep data sortedErlang

CassandraQuery languageRange queriesDatacenter/Rack awareHadoop integrationConfigurable cacheingLive schema changes

CassandraSome schemaGrowing cluster isn’t fair

HBaseCoprocessorsVersioned cells (BigTable)Hadoop integration

HBaseHadoopNameNode is SPoFSchema maintenance downtimeSchema required up frontComplicated balancing

http://www.flickr.com/photos/annguyenphotography/3267723713/No Silver Bullet

http://www.flickr.com/photos/nateone/3768979925 / HBase@gdusbabek

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Breaking the Relational Headlock: A Survey of NoSQL Datastores

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