Working with Amazon S3 Keys: 3 Critical Aspects


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Storage made for the internet; Amazon Simple Storage Service (Amazon S3) is designed to ensure easier web-scale computing. Amazon S3 has an intuitive interface that can be used to store and recover any measure of data, whenever, from any place on the web. 

It provides developers access to a similar exceptionally versatile, dependable, quick, and inexpensive data framework that Amazon utilizes to run its worldwide network of websites. Amazon S3 expects to expand the benefits of scale and to give those advantages to developers.

This blog talks about the critical aspects of Amazon S3 Keys. It starts with a brief introduction to the benefits of Amazon S3, followed by the various components of an Amazon S3 Bucket before diving into the details of working with Amazon S3 Keys. It wraps up with the guidelines and key considerations for naming Amazon S3 Keys.

Table of Contents

Understanding the Benefits of Amazon S3

The advantages of working with Amazon S3 are endless. This is because the platform is designed with a minimal feature that ensures simplicity and robustness. Take a look at some of the advantages of using Amazon S3.

  • Developers can create and name buckets that store data. Buckets in this context are data storage containers in Amazon S3. 
  • You get to store an unlimited amount of data by uploading as many objects as you like in the bucket with each object containing up to 5 terabytes of data. After storage, each object stored can be retrieved using a uniquely assigned key.
  • You’ll have access to your data. This means that you can download it whenever you want or share it with other users.
  • With a standard and intuitive interface that’s REST and SOAP enabled, Amazon S3 is designed to function with all internet-development toolkits.
  • Provide or deny access to other people who want to transfer or download data into your Amazon S3 bucket. Give transfer and download consents to three kinds of users. Validation features of Amazon S3 can help keep information secure from unapproved access.
S3 Key: Amazon S3 Working
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Understanding the Amazon S3 Components

Here are a few key Amazon S3 components that can be leveraged for optimizing workplace productivity:

1) Amazon S3 Buckets

S3 Key: Amazon S3 Bucket
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Buckets are containers for objects stored in Amazon S3. The bucket contains all the objects in the storage. For instance, let’s say you have the object named photos/puppy.jpg stored in the awsexamplebucket1 bucket in the US West Oregon Region, hence the address becomes

The bucket can be used for several things such as;

  • Organizing the Amazon S3 namespace.
  • Identifying the account in charge of storing and data transfer charges.
  • It manages access control.
  • It serves as the point of aggregation for usage reporting. 

To store an object, you make a container (bucket) and afterward transfer the object to the pail. At the point when the object is in the container, you can open it, download it, and move it. At the point when you presently don’t require an object or a container, you can tidy up your resources by deleting them.

2) Amazon S3 Objects

These are the basic elements stored in Amazon S3. They comprise object data and metadata. The data part is opaque to Amazon S3. While the metadata is a bunch of name-values that describe the object. These incorporate some default metadata, for example, the date of modification, and standard HTTP metadata, like Content-Type. You can likewise determine custom metadata at the time the object is stored.

Simply put, an object is a file (any type) and any metadata that describes the file. An Amazon S3 object comprises of the following:

  • Data: this can be anything (documents/zip/pictures/etc.)
  • A Key (key name): unique identifier
  • Metadata: Set of name-value that can be set while uploading an object and can no longer be changed after it has been successfully uploaded. To change metadata, Amazon S3 proposes to make an object duplicate and set the metadata again.

3) Amazon S3 Metadata

Every bucket object has fixed system metadata which is handled by Amazon S3.

The system metadata has 2 sets:

  • Metadata: This can refer to object creation date which is constrained by the system and exclusively Amazon S3 can change its value. 
  • Other Metadata: This can refer to the storage class designed for an object and the enabled server-side encryption objects, which are System Metadata with values constrained by you. 

Upon object creation, the following may be carried out: configuration of System Metadata object values, and updating the values when needed. 

4) Amazon S3 Keys

This is a distinctive identifier for an object stored in a bucket. With Amazon S3, each object stored in a bucket has one precise Amazon S3 Key. This means that every bucket can be identified with a bucket, version ID, and S3 Key. Hence, through a combination of the three above, every object can be addressed. For instance, in the URL:, “doc” is the name of the bucket, and “2021-06-28/AmazonS3.wsdl” is the S3 Key.

Working with Amazon S3 Keys

S3 Key: Amazon S3 Keys
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Object Keys or rather a key name identify each object in the bucket. While object metadata is a set of name-value pairs. At the point when you create an object, you determine the key name, which particularly recognizes the object in the bucket. 

For instance, on the Amazon S3 console, when you feature a bucket, a rundown of objects shows up that is in your bucket. The names you see are the Object S3 Keys. The name for each Object S3 Key is an arrangement of Unicode characters whose UTF-8 encoding is all things considered 1,024 bytes in length.

So this is how the Amazon S3 data model works; you create a bucket that stores objects. Somewhat a flat structure. Check this post by AWS to learn about how to create buckets and objects. However, there is no order of sub-buckets or sub-folders but you can assume logical hierarchy with the object key names prefixes. With the Amazon S3 console, it recognizes every object by delimiters and prefixes.

More so, if you upload an object on Amazon S3 with a key name that already exists in a versioning-enabled bucket, the system creates a new version of the object rather than replacing the existing object.

You can assume your bucket (admin-created) has four different objects with the following object S3 keys:

  • Entertainment/Projects.xls
  • Education/statement1.pdf
  • Bank/taxdocument.pdf
  • s3-dg.pdf

With the Amazon S3 console, every S3 Key name prefixes (Entertainment/, Education/, Bank/) and delimiter (‘/’) are used to present a folder structure. Because the last object s3-dg.pdf doesn’t have a prefix, it sits at the root level of the bucket. With this format, when you open any of the folders, you see the file in the object. 

Understanding the Guidelines for Naming Amazon S3 Keys

As opposed to other storage systems, certain characters used in Object Key names may not be accepted by the system. For instance, you are allowed to make use of UTF-8 characters in the key name. The following are considered safe characters for use in Object S3 Key names. 

Special Characters

  • Asterisk (*)
  • Close parenthesis ())
  • Exclamation point (!)
  • Forward slash (/)
  • Hyphen (-)
  • Open parenthesis (()
  • Period (.)
  • Single quote (‘)
  • Underscore (_)

Alphanumeric Characters

  • 0-9
  • a-z
  • A-Z

The following are instances of acceptable Object Key names:

  • 4my-organization
  • my.great_photos-2014/jan/myvacation.jpg
  • videos/2014/birthday/video1.wmv

The following characters may require that you handle them especially by using additional code handling and the possibility of a URL or HEX. They are characters that your browsers may not be handling so there’s a need for special handling.

  • Ampersand (“&”)
  • ASCII character ranges 00–1F hex (0–31 decimal) and 7F (127 decimal)
  • ‘At’ symbol (“@”)
  • Colon (“:”)
  • Comma (“,”)
  • Dollar (“$”)
  • Equals (“=”)
  • Plus (“+”)
  • Question mark (“?”)
  • Semicolon (“;”)
  • Space ( )

Here’s a list of characters you should avoid using. They are characters that require special handling across all applications for consistency: 

  • Backslash (“”)
  • Caret (“^”)
  • Grave accent / backtick (“`”)
  • ‘Greater Than’ symbol (“>”)
  • Left curly brace (“{“)
  • Left square bracket (“[“)
  • ‘Less Than’ symbol (“<“)
  • Non-printable ASCII characters (128–255 decimal characters)
  • Percent character (“%”)
  • ‘Pound’ character (“#”)
  • Quotation marks
  • Right curly brace (“}”)
  • Right square bracket (“]”)
  • Tilde (“~”)
  • Vertical bar / pipe (“|”)

Learn about the Amazon Redshift COPY Command which is the standard way of bulk inserting data from another source

Understanding the Key Considerations for Amazon S3 Key Allocation

Here a few things to keep in mind while using Amazon S3 Keys:

  • If an Object S3 Key name consists of a single period (.), or two periods (…), you can’t download the object using the Amazon S3 console.
  • To download an object with a key name of “.” or “.”, you must use the AWS CLI, AWS SDKs, or REST API.
  • Amazon S3 supports buckets and objects, and there is no hierarchy in Amazon S3. 
  • However, the prefixes and delimiters in an Object S3 Key name enable the Amazon S3 console and the AWS SDKs to infer hierarchy and introduce the concept of folders.
  • You can use any UTF-8 character in an Object Key name. However, using certain characters in key names may cause problems with some applications and protocols.


You have learned about the basics of Amazon S3 starting with its introduction and the importance of using this storage system. We likewise took a gander at buckets, objects, keys, and metadata. 

Using Object Keys can be a daunting task except you know what to do and what kinds of characters to use. Otherwise, you will encounter so many errors while uploading your object. This post likewise provided us with the types of characters that will be accepted by S3 and those that will be rejected. We also looked at some special characters that require special handling while naming Object Keys. 

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Samuel Salimon
Freelance Technical Content Writer, Hevo Data

Samuel specializes in freelance writing within the data industry, adeptly crafting informative and engaging content centered on data science by merging his problem-solving skills.

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