Introducing Today's Project!
What is Amazon DynamoDB?
DynamoDB is useful because it combines fast performance, flexible data modeling, and effortless scaling, making it a strong choice for modern applications that need to handle large amounts of varied data reliably.
How I used Amazon DynamoDB in this project
In today's project, I used Amazon DynamoDB to create tables, load diverse data like projects and videos into the ContentCatalog, and then view and update those items, because DynamoDB’s flexible schema allowed me to store different
types of content side by side while still retrieving them quickly with partition keys.
One thing I didn't expect in this project was...
One thing I didn't expect in this project is how straightforward it was to set up and run DynamoDB compared to relational databases like RDS or Aurora, because DynamoDB doesn’t require configuring servers, managing connections,
or defining rigid schemas, it just lets you create a table and start loading items right away.
This project took me about an hour, taking me through the full cycle of working with Amazon DynamoDB, creating tables, loading diverse data like projects and videos, and then viewing and updating items, because it was designed to show
how DynamoDB’s flexibility and speed make it easier to manage different types of content compared to traditional relational databases.
Create a DynamoDB table
DynamoDB tables organize data using items, which are records made up of attributes that describe details about each item; unlike relational databases, items don’t need to share the same attributes, giving DynamoDB a flexible way to store varied information in one table.
An attribute is a single piece of data that describes an item in DynamoDB, for example, if the item is a student record, attributes could include the student’s name, age, or number of projects completed. Unlike traditional relational databases where every row must share the same set of columns, DynamoDB
items can each have different attributes, giving you flexibility to store varied information within the same table.
Read and Write Capacity
Read Capacity Units (RCUs) and Write Capacity Units (WCUs) are DynamoDB’s measures of throughput, where RCUs define how many reads per second a table can handle and WCUs define how many writes per second it can handle.
Amazon DynamoDB’s Free Tier provides 25 GB of storage, along with 25 Read Capacity Units (RCUs) and 25 Write Capacity Units (WCUs), which together allow upto 200million of requests per month at no cost. I turned off auto scaling because while it can automatically increase capacity in production to handle
spikes in demand, it could push usage beyond the Free Tier limits and lead to unexpected charges, so disabling it ensures my table stays within the free allowance while I safely experiment.
Using CLI and CloudShell
AWS CloudShell is a browser‑based command line environment provided by Amazon Web Services that let's you securely manage, explore, and interact with your AWS resources without needing to install or configure tools locally. It comes pre‑authenticated with your AWS account and includes popular developer tools, making it easy to run commands, scripts, and manage services like DynamoDB directly from your web browser.
AWS CLI is a command-line interface tool that lets you manage and interact with AWS services by typing commands instead of using the web console. It provides a unified way to automate tasks, run scripts, and control resources like DynamoDB, S3, or EC2 directly from your terminal, making it especially useful for developers and administrators who want efficiency and repeatability in managing their cloud infrastructure.
I ran a CLI command in AWS CloudShell that created a new
DynamoDB table, because CloudShell provides a ready‑to‑use, browser‑based terminal that’s already authenticated with my AWS account, making it simple to execute AWS CLI commands without installing or configuring anything locally. This step is part of learning how to provision DynamoDB resources directly from the command line, reinforcing the idea that you can manage AWS services not only through the console but also programmatically
Loading Data with CLI
I ran a CLI command in AWS CloudShell that created new DynamoDB tables, because CloudShell comes pre‑installed with the AWS CLI and is already authenticated with my AWS account, making it easy to provision resources directly from the browser without needing any local setup. This step shows how DynamoDB tables can be defined programmatically, reinforcing the flexibility of managing cloud databases through commands instead of the console.
Observing Item Attributes
I checked a ContentCatalog item, which had the following attributes:
Id (partition key, number), Title (string), URL (string), Authors (list), Price (number), Difficulty (string), Published (boolean), ProjectCategory (string), and ContentType (string).
I checked another ContentCatalog item, which had a different set of attributes:
Id (partition key, number), Title (string), URL (string), VideoType (string), Price (number), Services (list, sometimes included), and ContentType (string).
Benefits of DynamoDB
A benefit of DynamoDB over relational databases is flexibility, because it doesn’t require a fixed schema, items in the same table can have different sets of attributes and data types. This means you can store diverse records (like projects and videos in your ContentCatalog) side by side without redesigning the table, whereas relational databases enforce rigid column structures that must be consistent across all rows. This flexibility makes DynamoDB especially useful for applications where data models evolve quickly or vary widely.
Another benefit over relational databases is speed, because DynamoDB is designed for high‑performance at scale, using SSD storage and a distributed architecture that allows single‑digit millisecond response times. Unlike relational databases, which often need complex joins and indexing across rigid schemas, DynamoDB retrieves items directly by their keys, making lookups and writes much faster. This speed is especially valuable for applications like gaming, e‑commerce, or real‑time analytics, where quick responses are critical.
🤝Next in the series builds on this, which is "Query Data with DynamoDB"
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