Skip to main content

One post tagged with "Database CI/CD"

View All Tags

· 3 min read

Blue elephants in skies

Today, developers who need to work with full scale data have three options:

  1. Develop scripts to backup & restore their production database
  2. Use expensive cloud provided database cloning features
  3. Deploy and test on production 😱

In other words, they can pay with time, money, risk, or some combination of all three.

But! There is a better, faster, cheaper, and completely safe way for developers to get the data they need to do their work properly. With the Database Lab Engine, developers can instantly provision as many full scale copies of their database as needed.

Check out this table which makes a direct comparison of the most common methods (We omitted testing on production. Don't do that.):

Provisioning TimeMonthly Compute CostsMonthly Storage CostsTotal Monthly Costs for 10 Clones
Traditional Thick Cloning (EC2 + EBS) Hours $185 $100 per clone $1185
EC2 + EBS restored from snaphot ~10 mins plus an hour for warmup (lazy load) $185 $100 per clone $1185
RDS Clones ~10 mins plus an hour for warmup (lazy load) $365 per clone $100 per clone $4650
Aurora thin clones ~5 mins $417 per clone $100 $4270 (+ IO costs)
Database Lab Engine thin clones ~5 seconds $345 $100 $445

The price comparison here makes the following assumptions:

  1. Once provisioned, the clone remains continuosly available for development and CI testing
  2. The clones all run on an r5.xlarge instance
  3. The database size is 100 GiB

As a result, running your development or staging environments with the Database Lab Engine (how it works) is more than 10x cheaper and 10x faster than the best available alternative.

Try it now in the AWS Marketplace. Setup docs are here and contact us if you have questions!

Share this blog post:

Dante Cassanego
Dante Cassanego

Postgres.ai

Database Lab
Database Lab by Postgres.ai

An open-source experimentation platform for PostgreSQL databases. Instantly create full-size clones of your production database and use them to test your database migrations, optimize SQL, or deploy full-size staging apps.