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Introduction to NoSQL and NewSQL
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NoSQL and NewSQLZhongke ChenMay 28, 2012
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Agenda
What’s NoSQL
Typical NoSQL Models
What’s NewSQL
Popular NoSQL and NewSQL DBMSes
Discussion
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Problems with SQL
Scale out
Performance & Size
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What’s NoSQLNoSQL is a term used to designate databases which differ from classic relational databases in some way.
It does not use SQL as its query language (no relational model, no JOIN)
It may not give full ACID guarantees
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ProsIt may have a distributed, fault-tolerant architecture
significant gains in performance for certain data models
It deals with huge quantities of data
Schema-less Design
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CAP TheoremSunday, June 3, 12
NoSQL Models
Key-Value
Column Family
Document
Graph
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NoSQL Models: Key-Value
key -> value
Examples: memcached, redis, Berkeley DB, Dynamo
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NoSQL Model:Column Family
Row key, Column key -> Value
Examples: BigTable, Cassandra, HBase
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NoSQL Model:Document
Key -> Document (JSON, XML)
Examples: MongoDB, CouchDB
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NoSQL Model:Graph
Examples: Neo4j, OrientDB
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What’s NewSQL
NewSQL preserves SQL and offer high performance and scalability, while preserving the traditional ACID notion for transactions.
Examples: VoltDB, NimbusDB, Clustrix, Drizzle
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RedisKey-Value
In-Memory Cache
Rich Data Types and Operations
Optional Persistence
Master-Slave Replication
Transaction
Use cases:
weibo.com
dianping.com
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MongoDBJSON like (BSON) Document Store
Auto Sharding
Global Lock, Only one node writable
Replica Sets Replication
Eventual Consistency
Mongo Query Language (Friendly to SQL users)
Use cases:
dianping.com
盛大
Cloud Foundry
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CouchDBJSON Document Store
Written in Erlang
Master-Master Replication
MVCC
Eventual Consistency
Compaction
Offline
HTTP/REST API
View (query tool)
Use cases:
Ubuntu One
Meebo
Some Facebook Apps
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CassandraColumn family model
Decentralized
Tunable Consistency
Use cases:
Netflix
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Neo4JGraph database
Small Footprint
Scalability
A powerful traversal framework
Cypher Query Language
Gremlin Traversal Language
Use cases:
Multi-level Marketing Engine
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VoltDBSpeak SQL
Stored Procedures
Partitioning Table and Replication Table
Lock free design
In-Memory
Snapshots and command logging
K-safety
Linear Scalability
Use cases:
http://voltdb.com/customers
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How To ChooseMongoDB: If you need dynamic queries. If you prefer to define indexes, not map/reduce functions. If you need good performance on a big DB. If you wanted CouchDB, but your data changes too much, filling up disks.
CouchDB: For accumulating, occasionally changing data, on which pre-defined queries are to be run. Places where versioning is important.
Redis: For rapidly changing data with a foreseeable database size (should fit mostly in memory).
Neo4J: For graph-style, rich or complex, interconnected data. Neo4j is quite different from the others in this sense.
Cassandra: When you write more than you read (logging). If every component of the system must be in Java. ("No one gets fired for choosing Apache's stuff.")
VoltDB: If you want to speak SQL and use JOIN
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Q&A
The End!
Thank you!
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