That's a fair point, and it's a known challenge with file-based backups on systems like Postgres. That said, some backup systems implement chunk-level deduplication and content-addressable storage, which can significantly reduce the amount of data actually transferred, even when large files change slightly.

For example, tools like Plakar (contributor here) split data into smaller immutable chunks and only store the modified ones, avoiding full re-uploads of 1GB files when only a few bytes change.

Thank you for mentioning it (Plakar here).

We are doing our best to complete existing solutions :)

Time to short Nvidia ?

Great insights! Has anyone here switched to a SaaS runner and seen real gains in speed or reliability?

I read the poem three times and still can’t decide if it’s about a cat or a cat about cats.

All I can say is that I'm flattered you considered my cat blurb to be a poem, I might revisit my career

Yes, both ptar and plakar. If you want to read more about the internal: https://www.plakar.io/posts/2025-04-29/kloset-the-immutable-...

That’s basically one of the reasons that led us to build Plakar.

S3 buckets can just vanish for lots of reasons. With AWS’s shared-responsibility model, you’re the one who has to back up and protect your data not AWS.

The hold in compliance mode with AWS is accepted way to persist data that a company obliged to hold legally by US requirements.

And if your company has a sale contract with AWS the buckets cannot just vanish or AWS cannot close the account at arbitrary moment.

AWS Backup can get really pricey since you pay GB-month for every single restore point. Plakar only charges once for the initial backup and then for the small deltas on whatever cheap storage you pick.

Also, AWS Backup locks your snapshots into AWS vaults, whereas Plakar lets you push and pull backups to any backend—local disk, S3, another cloud, on-prem, etc.

AWS backup is a bit more nuanced than that; ideally the thing you want is N days of PITR (point in time recovery) and you want that across all your data stores (RDS dbs, buckets, dynamodb tables, etc etc), and you want to be able to restore them all to a common point in time. 7 or 30 days or PITR are common choices. It is ideal if you can perform a data restore in 1 operation since your hair may be on fire when you need to use it. In practice almost all your recovery will be from this.

The storage needed for this depends on the data change rate in your application, more or less it works like a WAL in a DB. What is annoying is that you can't really control it (for obvious reasons), and less forgivably, AWS backup is super opaque about how much is actually being used by what.

Retention of dailies / weeklies / monthlies is a different (usually compliance) concern (NOT operational, not really, if you have to restore from a monthly your business is probably already done for) and in an enterprise context you are generally prevented from using deltas for these due to enterprise policy or regulation (yeah I know it sounds crazy, reqs are getting really specific these days).

People on AWS don't generally care that they're locked in to AWS services (else.. they wouldn't be on AWS), and while cost is often a factor it is usually not the primary concern (else.. they would not be on AWS). What often IS a primary concern is knowing that their backup solution is covered under the enterprise tier AWS support they are already paying an absolute buttload for.

Also stuff like Vault lock "compliance mode" & "automated restore testing" are helpful in box-ticking scenarios.

Plakar looks awesome but I'm not sure AWS Backup customers are the right market to go for.

Yes Plakar works much like Restic and Kopia: it takes content-addressed, encrypted and deduplicated snapshots and offers efficient incremental backups via a simple CLI. Under the hood, its Kloset engine splits data into encrypted, compressed chunks. Plakar main strengths:

UI: In addition to a simple Unix-style CLI, Plakar provides an web interface and API for monitoring, browsing snapshots

Data-agnostic snapshots: Plakar’s Kloset engine captures any structured data—filesystems, databases, applications—not just files, by organizing them into self-describing snapshots

Source/target decoupling: You can back up from one system (e.g. a local filesystem) and restore to another (e.g. an S3 bucket) using pluggable source and target connectors

Universal storage backends: Storage connectors let you persist encrypted, compressed chunks to local filesystems, SFTP servers or S3-compatible object stores (and more)—all via a unified interface

Extreme scale with low RAM: A virtual filesystem with lazy loading and backpressure-aware parallelism keeps memory use minimal, even on very large datasets

Network- and egress-optimized: Advanced client-side deduplication and compression dramatically cut storage and network transfer costs—ideal for inter-cloud or cross-provider migrations

Online maintenance: you don't need to stop you backup to free some space

ptar...

Thank you!