nosql databases

1. Demystfying Nosql
Databases
Mike King & Matt Thomas
Enterprise Technologists, Big Data

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What are databases?
• Tedd Codd & Chris Date
– 13 rules
– An Introduction to Database Systems
• Wikia/Wikipedia
• Mike
– An organized collection of data offering varying levels
of availability, scalability, performance, consistency,
management, accessibility and quality.
• Matt
Databases defined

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What types of databases
exist?
• Network – Adabas
• Hierarchical – IMS
• Relational – PostgreSQL
• Object Oriented – Versant
• Nosql – MongoDB, Hbase
• Newsql – VoltDB, MemSQL
• XML – MarkLogic, Xyleme

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Nosql background, issues and considerations
• History
– Google Big Table, Amazon Dynamo
• What does schema-less mean?
– On read
– Still structured
– Embedded
– Can vary between records
• Languages & formats used
– Java, Python
– JSON, BSON, XML, CSV

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Nosql background, issues and considerations
continued
• Eric Brewer’s CAP theorem
– Can’t do all three.
• What does NoSQL really mean?
– Distributed, shared-nothing aggregate oriented database
– “Not only SQL” versus “No”
• What are the factors for the various choices?
– Best fit
– Use case(s)
– KV
– HA, Multi-site
– Network
– Kevin Bacon
• Sharding
– Partitioning

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NewSQL
• SQL as predominant access method
• OLTP
• Larger user populations than nosql
• Better consistency than nosql
• Still subject to Brewer’s CAP theorem
• Examples
– VoltDB, MemSQL, Clustrix, NuoDB

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RDBMS or NOSQL?-tablify
• RDBMS
– Large user populations
– Structured
– Static schema
– Strong typing
– Access by PK, AK, indexes
– Complex structures
– Feature rich
– Multi-purpose, shared by apps
– OLTP
– ACID
– Complex queries
– >3 way joins
– Small to medium sized dbs
– COTS pkgs
– Datamarts
• Nosql
– Smaller user populations
– Multi-structured
– Schema evolution
– Weak typing
– Mostly random access by PK
– Simple structures
– Bare bones functionality
– Single purpose/use case, not shared by apps
– Not transactional
– BASE
– Simple queries
– VLDB
– Horizontal scalability

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NoSQL Database Types
• Four types
– Columnar
– Hbase, Cassandra
– Document
– MongoDB, Couchbase
– KV
– Riak, Redis
– Graph
– Neo4j, Titan
• How many do you need?
– By type
– Within type
• Who will manage them?
– DBAs
• How do you access them?
– SQL, nosql
– Sequential

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Nosql Commonalities
• Mostly open source
• Weak typing
• Multi-structured
• Horizontal scale
• No standardization
• VLDB
• Single purpose, per database

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Nosql Differences
• Access
• Formats supported
• Features
• Management
• Administration
• VLDB
• Performance & tuning
• Resource consumption
• Language bindings
• APIs
• Security
• Persistence
• Programmability
• ?Schemas

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How are nosql databases typically used?
• As an adjunct to Hadoop
• As a partial replacement for some RDBMS workloads
• To scale linearly
• As a data store for semi-structured and multi-structured data

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What questions do our customers ask?
• Why is my Hbase cluster so CPU hungry?
• Do you have an RA for <Your favorite nosql db goes here>?
• Can I replace all my Oracle databases w/ some nosql databases?

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What are some common problems?
• Cohabitation with Hadoop and other programs on a cluster.
• Poor db design
• Falling prey to vendor hype

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How about some general recommendations?
• Read a book or two on your target nosql db.
• Search thru the blogosphere & twitterverse.
• Don’t use more than one type, unless you’re an SI or large service provider.
• If performance & service levels are important isolate the cluster.
• Review your database design w/ DBAs & those that have done it already.
– Presentations, conference proceedings, boutique consultancies

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Nosql Examples, Diving Deeper
• Hbase
• MongoDB
• Redis
• Neo4j

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Hbase
• Columnar
– Column families
• Uses ZK
• Has a master
• WAL
• Region servers
• Memstore
• Hfiles
• HDFS
• Uses jvm heap
• Access
– Row key
– Get
– Put
– Scan
– Bulk load
• Design
– Beware of skew
– Tune for peaks
• Perf
– CPU intensive
– Very fast for puts & gets by key

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Neo4j
• Property graph
– Nodes, edges, relationship/arc, direction, data/properties(node & arc)
– Edge labeled multi-digraph
• REST API
• ACID
• Fast, scaleablable lookups
• Lucene index for search

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Our Contact Info
• Mike_King2@dell.com
• @MikeDataKing
• 901-262-7918
• Matt_Thomas@Dell.com
• ?twitter?
• 904-429-6709