True Elasticity of Oracle Autonomous Database

Scaling Autonomous Database on OCI

Original Post First Appeared on my Medium Blog :


Oracle’s Autonomous Database is a massively scalable serverless database available exclusively on Oracle Cloud Infrastructure. It is build on the proven reliability & maturity of the Oracle database over the last four decades. However nothing about it based on antiquity, It is a true serverless and elastic offering for persisting data for cloud native apps. You don’t need to provision any node types or define the number of nodes, just scale your opcu’s (virtual cores) and storage in increments of 1Terabyte and you are good to go. It can even scale automatically based on utilisation. It comes in 4 different flavours and 2 deployment models ; Data Warehouse, Transaction Processing, JSON, Low Code Development; with Shared Infrastructure or Dedicated Infrastructure as the deployment choice.

Having worked with the Oracle Autonomous Database since it was launched in 2018. I’ve been an ardent advocate of how both Enterprises and Startups can reap the benefits of running a truly cloud scale database. To prove it’s ability to provide a massively scalable persistent database for internet scale apps as well as Enterprise apps, I decided to perform a test to stretch (no pun intended) it’s elasticity.

Oracle Autonomous Database

Chronological transcribe on how I scaled the Oracle Autonomous Datawarehouse from 1 ocpu with 1TB of storage to 100 ocpu’s with 100TB of Storage and back; scaling both the compute and storage to 100x capacity and back.

So let’s get started

Initial Start State — State 1

We start with 1 TB of Storage with 1 ocpu

You can run most of your small projects on 1TB and 1 ocpu. But now let’s get adventurous and start scaling it up.

State 2 — Scale 30x Capacity

We are going for 30 ocpu’s with 30 TB of Storage. Enough size to accommodate your medium sized workloads and would suffice on most if not all Enterprise Data warehouses which hold structured data.

Here we go…

Wait what !? It scaled 30x in approximately 50 seconds. Yes you read that correct, it scaled up a Data warehouse to 30 times it’s compute and storage capacity in under a minute.

Here’s what the end result of state two looks like

State 3— Scale to 100x Capacity

Now we will start making things really interesting. We are going for a target of 100 ocpu’s with 100 TB of storage. So from our first state we are going for a 100x storage and compute increase. I had no hopes of this finishing as quickly, I was prepared to wait for atleast 30mins before it would return a success or failure. But once again Autonomous just completely surprised me ..

Have a peak at the start and stop times

It went from 30 ocpu’s with 30TB to 100TB with 100 ocpu’s in 63 seconds. Yes you read that correct! All this while your ETL jobs continue running and your BI dashboards keeps serving your end-users..

If you calculate the sum of of State 1 to State 3 transition, we are talking about a 100 times capacity increase in compute and storage in less than 2 minutes (113 seconds total). That is just mind numbing performance. I’ve not yet come across any cloud data warehouse which can increase it’s capacity while running your applications and scaling up the compute and storage so rapidly.

Final Transition — Back to State 1

Scaling up is all well and good but many cloud providers always speak of scaling up when speaking of elasticity, but true elasticity is scaling-up and scaling down. So in our final transition we will scale down the Autonomous database back to the state we started at i.e State 1

In the final transition we scale down from 100 ocpu’s, 100TB storage to 1 ocpu with 1TB storage.

Scaling back took about 3 mins 47 seconds. Still impressive considering it took away 100 times the capacity.

State Transition Summary

State Transition Timings

Final Run
As a final test I wanted to test scaling directly from 1 ocpu + 1 TB to 128 ocpu with 120TB storage directly without any cooling down period.

Result : 59 seconds to scale to 128 opcus with 120 TB’s of storage from 1 ocpu + 1TB. 128x compute scale-up and 120x storage scale up in under a minute. Just amazing!

State Transition — Final Run


It was an astonishing run and an amazing result. It took 1 min 53 seconds to scale 100x and 3 mins 47 seconds to scale back down. In total of 5 minutes 40 seconds we went 100 times the compute and storage size and back in 2 increments. And without a cooling period we were able to scale up from 1 ocpu, 1 TB to 128 ocpu’s and 120TB storage in a mere 59 seconds.

This was a real world run with no pre-provisioned capacity, it just shows how truly elastic the Autonomous database is.

I hope you saw the benefit of running the Oracle Autonomous database for growing your business without worrying about capacity. No matter how “big” the data requirements, you can attain capacity in the Oracle Cloud at the click of a button.


[1] The Autonomous database is available to try in an Always Free account which gives you two Autonomous databases with 20GB of Storage and 1 ocpu each. You can always convert your always free account to a paid account whenever you are ready to scale 100x 🙂

[2] This test was not supported by Oracle or any of the internal Oracle teams to ensure capacity is readily available. It was a completely spontaneous test for a proof of concept of Autonomous Database.

[3] Test was conducted in OCI – Australia East (Sydney) region.

Category: CloudDatabaseOracle


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Article by: Shadab Mohammad