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[B] NoSQL, [C] CAP-Theorem, [E] Eras of Databases, [F] Database Paradigms,…
[B] NoSQL
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[3] Design Goals
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Make existing massive, unstructured, data mounts usable.
[6] Sources of Data
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Social Media, Data Services
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[C] CAP-Theorem
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Partition Tolerance
the system has to continue working, even under arbitrary network partitions
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[F] Database Paradigms
Relational
- Mature ACID
- Does not Scale
- Need to defined data model first
- Tables
Examples
Oracle, MySQL,
PostgreSQL,
Microsoft SQL
Server, IBM DB/2
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Key-Value
Examples
Berkley DB,
Memcache,
DynamoDB, S3,
Redis, Riak
Memcached
Open source, In-memory key-value store
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Quick, Ease of Deployment and Development
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Riak
Open source, Dynamo-inspired key-value store
Focus on availability, fault-tolerance, simplicity, scalability
Replication, auto-sharding, failure recovery
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Redis
Open source, in-memory key value store with optional durability
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Support these datatypes: simple lists, sets and hashes
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Blazingly fast and easy to
scale (no joins, no indexes)
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Column-Family
BigTable Systems
Examples: Google BigTable, HBase, Hypertable
Use a combination of row and column information as part of their key
E.g., Excelsheets
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