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Postgres is a database. Like Oracle is a database, this is a database.
We replaced our Oracle paid database with the open-source Postgres database, and we migrated around 50 lakhs of consumer data there with different rows and tables. We deployed this in different production staging and testing. We created three deployments, and each deployment has three servers.
Earlier, we were using the Oracle paid database, which is a commercial product. Then we switched to open-source due to the fact that we have lots of new projects and we could not handle the licensing costs. So we migrated our data from the Oracle Database Server to the Postgres Server. It helped us to evaluate the cost. We saved lots of money in terms of licensing.
It is open-source.
It provides the database load-balancing capability itself. It has data, like Pgpool, an open-source database, and a load balancer also.
We can also create the cluster in between the database in active, standby mode.
The solution is stable.
It's scalable.
It doesn't have any GUI-based monitoring tools. Oracle has some proprietary tools for monitoring all the databases and all that. Postgres doesn't have any graphical capabilities where we can monitor the database. We have to do it with the Sierra stuff and run some random commands. Then we can get the data from the cluster and databases table.
The initial setup is complex.
It would be ideal if they could provide an active cluster in Postgres. If one primary DB goes down, it should automatically fail over to the second database.
We've been using it for four years. I've used it since around 2018.
It's stable. There are no bugs or glitches. It doesn't crash or freeze. It's reliable.
It is very scalable.
From the user's perspective, we have around 500 users. However, we have around 50 lakhs of consumer records in the solution.
We plan to increase usage. We already added the sponsors, and we require the capacity and the transactional processing. Therefore, it's scalable. We don't have any licensing restrictions, so we can add on as required.
While we don't have technical support, we do have creative support. They are quite good.
Positive
We used to use Oracle Database.
We required lots of planning during the initial setup. The migration phase is very complex when you move from Oracle to Postgres. The installation and configuration have a moderate amount of difficulty.
The deployment and maintenance require three people, including one system administrator and two database administrators.
We handled the initial setup in-house. We didn't need any outside assistance.
We haven't invested any money into the solution and therefore haven't looked into ROI.
We have zero licensing costs. The solution is open-source.
We also evaluated some parts of MySQL. However, we didn't find it very suitable and scalable.
You need to be clear about your use cases and the transactional requirement you are observing from the database architecture before beginning with this solution. You need to consider your architecture based on the scalability and reliability of the applications. You need to take this into account before deploying any solution to Postgres.
I'd rate the solution eight out of ten.
We were using it as a high-volume text messaging solution.
It's fully open source, has a high throughput, and the serviceability is good.
This solution struggled with multi-regional synchronization.
The stability of this solution was very good.
The scalability was good. It's very comparable to the other databases on the market. We were doing 5,000 transactions a second, and probably one third of those were unique users at any one time.
The tech support was fine. We rarely needed to use it.
The setup was pretty straightforward, just standard database install stuff.
For maintenance, we had a single DBA, and a couple of people on our software development team served as their backups.
On a scale of one to five, with five being the most competitive pricing, I would rate this solution as a four.
We were using SQL Server in some circumstances, and the two solutions are very comparable, other than one being open source and one not. We've also used Cassandra, Bitquery, and a whole bunch of others. Each solution has unique advantages and disadvantages. From a feature standpoint, this solution is relatively close to parity in the environment. It stands out because it's opensource and cost effective, and it does everything pretty well.
For those looking into implementing this solution, my advice would be to think about how you want to handle multi-regional replication.
I would rate this solution as an eight out of ten.
