How to Choose Amazon Redshift over Oracle in PostgreSQL

Why choose Amazon Redshift over Oracle?

Opt for Amazon Redshift instead of Oracle to gain elastic column-store analytics, PostgreSQL-compatible SQL, and lower admin overhead with pay-as-you-go pricing.

Welcome to the Galaxy, Guardian!

Oops! Something went wrong while submitting the form.

Description

Example H2

Example H3

Why pick Redshift instead of Oracle?

Redshift delivers petabyte-scale columnar storage, automatic compression, and massively parallel query execution, making large analytic workloads faster and cheaper than Oracle’s row-store engine.

Its PostgreSQL 8.0-compatible dialect lets teams reuse existing SQL and tooling while avoiding Oracle-specific PL/SQL lock-in.

Fully managed clusters, automatic patching, and pause/resume remove routine DBA tasks and cut operational cost.

How does Redshift pricing compare?

Redshift charges per second for compute and per GB for storage, enabling cost control by resizing or pausing clusters—unlike Oracle’s perpetual licenses and support contracts.

What migration paths exist?

Use AWS Schema Conversion Tool (SCT) for DDL translation, then unload Oracle data to Amazon S3 and load it into Redshift with the COPY command.

Is SQL syntax different?

Core SELECT, JOIN, and window functions remain the same.Replace Oracle sequences with Redshift IDENTITY and use DISTKEY/SORTKEY for distribution and sort order.

When is Oracle still better?

Choose Oracle for high-volume OLTP requiring consistent sub-millisecond writes, rich PL/SQL packages, or on-prem regulatory constraints.

Best practices after switching

Define DISTKEY on high-cardinality join columns such as Orders.customer_id. Apply SORTKEY on order_date for time-series queries. Monitor with Amazon CloudWatch and apply automatic table vacuum.

Why How to Choose Amazon Redshift over Oracle in PostgreSQL is important

How to Choose Amazon Redshift over Oracle in PostgreSQL Example Usage


-- Analyze average customer spend after migration
SELECT c.name,
       ROUND(SUM(o.total_amount),2) AS lifetime_value
FROM   Customers c
JOIN   Orders    o ON o.customer_id = c.id
GROUP  BY c.name
ORDER  BY lifetime_value DESC
LIMIT 10;

How to Choose Amazon Redshift over Oracle in PostgreSQL Syntax


-- Create target table in Redshift
authenticate to redshift;
CREATE TABLE Orders (
    id          BIGINT IDENTITY(1,1),
    customer_id BIGINT   DISTKEY,
    order_date  DATE     SORTKEY,
    total_amount NUMERIC(10,2)
);

-- Bulk load from S3 (data exported from Oracle)
COPY Orders
FROM 's3://my-bucket/oracle_exports/orders_*.csv'
CREDENTIALS 'aws_iam_role=arn:aws:iam::123456789012:role/RedshiftCopy'
CSV DATEFORMAT 'YYYY-MM-DD';

-- Compare: Oracle equivalent bulk load
-- (External Table + INSERT)

Common Mistakes

Ignoring distribution style. Loading all tables with DISTSTYLE AUTO can cause data skew. Fix by setting DISTKEY on join columns like Orders.customer_id.
Using Oracle’s row-based indexing concepts. Redshift relies on SORTKEYs and compression instead of B-tree indexes. Define SORTKEY on query filters and run ANALYZE.