• Hosted, scalable database service by Amazon with the data stored in Amazons cloud.
  • Infinitely scalable, with minimal provisioning.
  • Managed, closed source DB.
  • Key-value, schema less DB.
  • ACID complaint.
  • Replication: Peer-based, master-master replication (though it is managed by AWS)
  • Concurrency: Vector Clocks
  • Sharding: Yes
  • ✅ Main Differentiator: Highly Available
  • ❌ Query-ability : table needs to be designed based on access pattern, as it gets difficult to change in the end.
  • Db-engines link

Data Types

Scalar Data Types

Type Symbol Description JSON Example
String S typical string "S": "this is a string"
Number N Any int or float "N": "98", "N":"3.141592"
Binary B Base64 encoded binary data "B": "nwaafrafs"
Boolean BOOL true or false "BOOL": false
Null NULL use for missing values "NULL": true

Set and Document Data Types

Type Symbol Description JSON Example
String Set SS Set of string “SS”: [“Prakash”, “Natarajan”]
Number Set NS Set of numbers “NS”: [“1”, “2”]
Binary Set BS Set of Binary “BS”: [“wsfawefa===”]
List L List that can consist of any scalar type “L” : [{“S”:”prakash”},{“N”:”1”}]
Map M key-value store with string as keys and any scalar as value “M”:{“key”:{“S”:”value”}}


  • Partition based schema
    • performs best when access to partition keys is balanced.

Hot spots

  • degrade performance and should be avoided.
  • partition key should not be clustered around few values.
  • composite key: aim for fewer partition keys and more range keys.

Key Types

1) Partition key (hash key)
2) Composite Key (partition key + Sort key)


Local Secondary Index

  • same (partition) hash key, different sort key.
  • need to be created at table creation

Global Secondary Index:

  • Any column.
  • can be created and modified anytime.
  • Pay for storage for that index.