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NoSQL and AWS Dynamodb

NoSQL and AWS Dynamodb



Slides presenting a little explanation about NoSQL and AWS DynamoDB

Slides presenting a little explanation about NoSQL and AWS DynamoDB



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    NoSQL and AWS Dynamodb NoSQL and AWS Dynamodb Presentation Transcript

    • AWS DynamoDB @nbluis http://about.me/nbluis
    • What ? • Database • NoSQL • AWS • SaaS
    • What ? •Database • NoSQL • AWS (IaaS, Paas)
    • What is a database ? Dammit! This is not for you!
    • What ? • Database •NoSQL • AWS (IaaS, Paas)
    • What do you mean?
    • NoSQL vs NewSQL • NoSQL is a really bad label • It’s not about SQL • It’s about better performance or scalability • Sometimes we can live without ACID
    • ACID ?
    • ACID
    • The cap theorem It’s impossible to simultaneously provide Availability Consistency Partition tolerance
    • Without partition tolerance guarantee We can be available (the data) and consistent RDBMS: Oracle, Postgres, MySQL, SQLServer, etc.
    • Without availability guarantee We can be highly scalable Big Table, Hypertable, HBase, MongoDB, Berkley DB, Memcache, Redis
    • Without consistency guarantee We can be highly replicable DynamoDB, Voldemort, Cassandra, SimpleDB, CouchDB, Riak
    • NoREL • ACID & JOINS are considered relational (unsupported) • Key-Value model • Column-oriented model • Document-oriented model
    • What ? • Database • NoSQL •AWS (IaaS, PaaS)
    • AWS
    • AWS • IaaS (Infrastructure as a Service) • PaaS (Platform as a Service) • Full managed DynamoDB service • Pay-as-you-go
    • DynamoDB • Fast • Full managed • Coast effective • Pay by throughput (reserved)
    • The good parts • Table based (each table is independent) • Schema free (except the Key) • Really fast to find using Primary and Range Keys • Support for complex queries (Scan)
    • The “must know” parts • Eventual consistency by default, with high costs to ensure consistency. • Must use SDK/API to access • 64K is the max “row” size • Complex queries are made using Sequential/Full Table Scan (high cost)
    • The bad parts • Very limited data types (text, number, binary) • No way to join tables • More than 64k of data per item requires “workarounds” • It’s not possible to copy a table to another one
    • Final considerations Pros: • Really fast using IDs • Really cost effective • Full managed is a good idea • A good option for key-value situations Cons • Very limited with types and joins • Complex queries are costly
    • Thanks! @nbluis http://about.me/nbluis