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.