Heroku PostgreSQL Crane DB vs Linode 1GB with PostgreSQL installed

I'm trying to decide between using the Heroku Crane PostgreSQL database ($50/month - https://postgres.heroku.com/pricing) or setting up a Linode 1GB Ram / 8 CPU / 48GB Storage / 2TB Transfer instance with PostgreSQL installed ($20/month - https://www.linode.com/).

I know that from a management perspective, using Heroku Crane PostgreSQL would be much easier, as everything is managed with security and backups taken care of.

What I was curious about is how performance of the two databases would compare. With the Linode 1GB / 8 CPU instance, only my database will be used on it. I see with Heroku Crane that it says it only gets 400 MB RAM. It also isn't clear with Heroku Crane how many CPU's I get and whether its a dedicated instance.

Does the Heroku DB manages the RAM/Cache of the DB more efficiently? Its unclear to me whether the Linode PostgreSQL instance would automatically use the 1GB RAM available to it efficiently, or if it would require custom setup on my part to ensure the DB is loaded into RAM.

If it is that the Heroku DB would be less performant for the money, but is a better deal because security, backups and management are taken care of, that is probably acceptable, I just want to understand the tradeoffs.

Thanks for any info people can provide. I'm new to DB management, and have been using a Linode 1GB instance with PostgreSQL installed for development and testing, but now that I'm going to production, am questioning whether to move over to Heroku Crane. Also, not sure if this matters, but my server is hosted through Heroku web instances.


Lower Heroku plans are on a shared server partitioned into containers with LXC. The details are on Heroku's site. Your plan appears to be one of them.

This can actually be a win as discussed in this question if you happen to be on an instance where other users aren't putting much load on the server. It makes your performance less predictable though.

The only good way to characterize performance is to benchmark with a simulation of your production workload.

Whether the RAM actually matters or not depends on your data. If your frequently accessed data and indexes fit in RAM on one machine, but not on another, then the RAM difference will make a huge difference. If the data fits in RAM on both hosts there's little benefit to adding RAM. If the hot data won't fit in RAM on either machine then disk I/O performance becomes more important than RAM, mostly random read I/O and the fsync() flush rate.

So. Benchmark with a simulation of your workload with your expected data size and see.

Heroku discusses cache in more detail here.

(I work for another company in the same kind of space as Heroku, per my profile, so I'm reluctant to express a strong opinion one way or the other).

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