Chapter 1. Getting Started
Amazon DynamoDB is a fully managed, cloud-hosted, NoSQL database. It provides fast and predictable performance with the ability to scale seamlessly. It allows you to store and retrieve any amount of data, serving any level of network traffic without having any operational burden. DynamoDB gives numerous other advantages like consistent and predictable performance, flexible data modeling, and durability.
With just few clicks on the Amazon Web Services console, you are able create your own DynamoDB table and scale up or scale down provision throughput without taking down your application even for a millisecond. DynamoDB uses Solid State Disks (SSD) to store the data which confirms the durability of the work you are doing. It also automatically replicates the data across other AWS Availability Zones, which provides built-in high availability and reliability.
In this chapter, we are going to revise our concepts about the DynamoDB and will try to discover more about its features and implementation.
Before we start discussing details about DynamoDB, let's try to understand what NoSQL databases are and when to choose DynamoDB over Relational Database Management System (RDBMS). With the rise in data volume, variety, and velocity, RDBMSes were neither designed to cope up with the scale and flexibility challenges developers are facing to build the modern day applications, nor were they able to take advantage of cheap commodity hardware. Also, we need to provide a schema before we start adding data, and this restricted developers from making their application flexible. On the other hand, NoSQL databases are fast, provide flexible schema operations, and make effective use of cheap storage.
Considering all these things, NoSQL is becoming popular very quickly amongst the developer community. However, one has to be very cautious about when to go for NoSQL and when to stick to RDBMS. Sticking to relational databases makes sense when you know that the schema is more over static, strong consistency is must, and the data is not going to be that big in volume.
However, when you want to build an application that is Internet scalable, the schema is more likely to get evolved over time, the storage is going to be really big, and the operations involved are okay to be eventually consistent. Then, NoSQL is the way to go.
There are various types of NoSQL databases. The following is the list of NoSQL database types and popular examples:
- Document Store: MongoDB, CouchDB, MarkLogic
- Column Store: Hbase, Cassandra
- Key Value Store: DynamoDB, Azure, Redis
- Graph Databases: Neo4J, DEX
Most of these NoSQL solutions are open source except for a few like DynamoDB and Azure, which are available as a service over the Internet. DynamoDB being a key-value store indexes data only upon primary keys, and one has to go through the primary key to access certain attributes. Let's start learning more about DynamoDB by having a look at its history.
