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Aug 24, 2026

Amazon Redshift Storage: Architecture, Types, RA3 & Managed Storage

Unlike Amazon Athena, Amazon Redshift physically stores data inside the data warehouse. It is designed specifically for Online Analytical Processing (OLAP) workloads and uses Massively Parallel Processing (MPP) along with columnar storage to achieve high query performance.



1. Stores Data

What does it mean?

Amazon Redshift is a database, meaning it physically stores your tables and data.

For example:

CREATE TABLE sales (

   sale_id INT,

   customer_id INT,

   amount DECIMAL(10,2),

   sale_date DATE

);

When data is loaded,

COPY sales

FROM 's3://company-data/sales/'

IAM_ROLE 'arn:aws:iam::123456789012:role/redshift-role'

FORMAT AS PARQUET;

the data is copied into Redshift's storage.

Unlike Athena,

  • Athena → reads data directly from S3.

  • Redshift → stores data inside the warehouse.

Internal Architecture

               Client

                  │

                  ▼

         Amazon Redshift

        -------------------

        sales table stored

        customer table stored

        product table stored

        inventory table stored

The data remains inside Redshift until:

  • DELETE

  • TRUNCATE

  • DROP TABLE

  • VACUUM (reclaims deleted space)

Interview Point

Redshift is a storage + compute engine. 

Athena is only a query engine.

2. Columnar Storage

If you execute >> SELECT SUM(salary) FROM sales;

Redshift reads only Salary Column instead of the entire row. This reduces disk I/O dramatically.

Advantages

✓ Reads only required columns

✓ Faster aggregation

✓ Better compression

✓ Less disk I/O

✓ Ideal for analytics

Columnar storage is one of the biggest reasons Redshift performs much faster than traditional row-oriented OLTP databases for analytical queries.

3. Compression

Because each column stores similar data types, compression becomes extremely effective.

Why compression is effective

Since every column contains similar values, patterns are easier to compress than in row storage.

Benefits

✓ Less storage

✓ Faster disk reads

✓ Better cache utilization

✓ Reduced network transfer

Compression Types

Redshift automatically selects the best encoding.

Common encodings include:

  • AZ64

  • LZO

  • ZSTD

  • BYTEDICT

  • DELTA

  • RUNLENGTH

Most modern Redshift clusters use Automatic Table Optimization, which chooses encodings automatically.

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