Amazon DynamoDB

What is NoSQL

  • NoSQL databases are non-tabular databases and store data differently than relational tables
  • NoSQL databases store data in documents (ex: json) rather than relational tables
  • NoSQL databases do not support join
  • NoSQL databases scale horizontally
  • Benefits of NoSQL Databases
    • Flexible data models
    • Horizontal scaling
    • Faster queries
    • Easy to work

NoSQL Database

  • Most-popular types of NoSQL database
    • Document databases
    • Key-value stores
    • Wide-column databases
    • Graph databases
  • Popular NoSQL Databases
    • MongoDB
    • Couchbase
    • Redis
    • Amazon DynamoDB
    • IBM Cloudant
    • RavenDB
    • Cassandra
    • HBase
    • Azure Cosmos DB

Amazon DynamoDB

  • Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale.
  • Single-digit millisecond performance at any scale
  • Millions of requests per seconds, trillions of row, 100s of TB of storage
  • Each table has a primary key
  • Each table can have an infinite number of items
  • Maximum size of a item is 400KB
  • Data types supported are:
    • Scalar Types: String, Number, Binary, Boolean, Null
    • Document Types: List, Map
    • Set Types: String Set, Number Set, Binary Set

Components of Amazon DynamoDB

  • The core components of DynamoDB are tables, items, and attributes
  • A table is a collection of items, and each item is a collection of attributes.
  • DynamoDB uses primary keys to uniquely identify each item in a table and secondary indexes to provide more querying flexibility.
  • Tables: A table is a collection of data. DynamoDB stores data in tables.
  • Items: Each table contains zero or more items. An item is a group of attributes that is uniquely identifiable among all of the other items.
  • Attributes: Each item is composed of one or more attributes. An attribute is a fundamental data element, something that does not need to be broken down any further.


DynamoDB – Primary Keys

  • When you create a table, table name and the primary key will be given.
  • The primary key uniquely identifies each item in the table, so that no two items can have the same key
  • DynamoDB supports 2 types of primary keys
    • Partition key
      • A simple primary key, composed of one attribute known as the partition key
    • Partition key and sort key
      • A composite primary key, composed of two attributes. partition key and sort key.
      • The combination must be unique

DynamoDB – Provisioned Throughput

  • Table must have provisioned read and write capacity units
  • Read Capacity Units (RCU): throughput for reads
  • Write Capacity Units (WCU): throughput for writes
  • Option to setup auto-scaling of throughput to meet demand
  • ReadCapacityUnits
    • The maximum number of strongly consistent reads consumed per second
  • WriteCapacityUnits
    • The maximum number of writes consumed per second

DynamoDB – Write Capacity Units

  • One write capacity unit represents one write per second for an item up to 1 KB in size.
  • If the items are larger than 1 KB, more WCU are consumed
  • Example 1: we write 10 objects per seconds of 2 KB each.
    •   We need 2 * 10 = 20 WCU
  • Example 2: we write 6 objects per second of 4.5 KB each
    • We need 6 * 5 = 30 WCU (4.5 gets rounded to the upper KB)
  • Example 3: we write 120 objects per minute of 2 KB each
    • We need 120 / 60 * 2 = 4 WCU

DynamoDB – Read Capacity Units

  • One read capacity unit represents one strongly consistent read per second, or two eventually consistent reads per second, for an item up to 4 KB in size.
  • If the items are larger than 4 KB, more RCU are consumed
  • Example 1: 10 strongly consistent reads per seconds of 4 KB each
    •   We need 10 * 4 KB / 4 KB = 10 RCU
  • Example 2: 16 eventually consistent reads per seconds of 12 KB each
    •   We need (16 / 2) * ( 12 / 4 ) = 24 RCU
  • Example 3: 10 strongly consistent reads per seconds of 6 KB each
    •   We need 10 * 8 KB / 4 = 20 RCU (we have to round up 6 KB to 8 KB)

DynamoDB – Write, Delete Data

  • PutItem – Write data to DynamoDB
  • UpdateItem – Update data in DynamoDB
  • DeleteItem
    • Delete an individual row
    • Ability to perform a conditional delete
  • DeleteTable
    • Delete a whole table and all its items
    • Much quicker deletion than calling DeleteItem on all

DynamoDB – Batching Writes

  • BatchWriteItem
    • Up to 25 PutItem and / or DeleteItem in one call
    • Up to 16 MB of data written
    • Up to 400 KB of data per item
  • Batching allows you to save in latency by reducing the number of API calls done against DynamoDB
  • Operations are done in parallel for better efficiency

DynamoDB – Reading Data

  • GetItem:
    • Read based on Primary key
    • Primary Key = HASH or HASH-RANGE
    • Eventually consistent read by default
    • Option to use strongly consistent reads (more RCU – might take longer)
    • ProjectionExpression can be specified to include only certain attributes
  • BatchGetItem:
    • Up to 100 items
    • Up to 16 MB of data
    • Items are retrieved in parallel to minimize latency

Amazon DynamoDB Accelerator (DAX)

  • It is a fully managed, highly available, in-memory cache for Amazon DynamoDB that delivers up to a 10 times performance improvement—from milliseconds to microseconds—even at millions of requests per second.
  • DAX does all the heavy lifting required to add in-memory acceleration to your DynamoDB tables, without requiring developers to manage cache invalidation, data population, or cluster management.
Amazon DynamoDB

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