Swytch vs Postgres/MySQL

If you’re running Postgres or MySQL as your primary SQL database and it’s working — keep running it. For the overwhelming majority of applications, switching to Swytch is the wrong call, even if Swytch is technically capable and even if the architectural differences look compelling on paper.

The rest of this page covers why, when the answer is different, and how to think about Swytch alongside Postgres or MySQL rather than instead of them.

Postgres turns thirty this year. MySQL is a couple of years younger. Between them, they run a substantial fraction of the internet’s business logic — banking, healthcare, ecommerce, government systems, SaaS platforms at every scale. Every terrible thing that could happen to a SQL database has happened to one of them, in production, and the person it happened to wrote a blog post about it.

That’s not a small thing.

When your database catches fire at 3am, there is a Stack Overflow answer for exactly your flavor of fire. There is a pg_stat_activity query that will show you the deadlock. There is a MySQL configuration flag that fixes the replication lag you just discovered. There is an experienced DBA on your team, or available to hire, who has seen this specific problem before and will tell you the first thing to check. There is a book on your shelf about performance tuning that covers your exact workload shape. There is a monitoring tool that was built for this database by someone who cared deeply about it.

Swytch doesn’t have that … yet. We’ve not run into the edge cases people have hit in production, the postmortems written, the tools built by communities who got burned once and never wanted to again. That kind of institutional depth only comes from years of real-world use. Postgres has that depth. MySQL has that depth. Everything younger, Swytch included, is still earning it.

The practical consequence: when something goes wrong with Postgres or MySQL, you have a playbook that spans decades of collective experience — people on your team, people you can hire, tools built by communities that have been through your exact failure before. Swytch doesn’t have that institutional depth yet, by definition. The longer it runs in production, the more of that accrues, but there’s no way to skip ahead.

If your workload can be served by a single Postgres or MySQL (or a primary + replicas), the playbook argument is overwhelming. Don’t trade a boring, known-failure-mode database for an interesting one. The boring one is paying your paycheck.

Run down this list. If any of these describe you, don’t switch.

Your data fits in one region. If every user of your application is served well enough by a database in a single region — which is most applications — the reason to use Swytch doesn’t apply. Run Postgres. Run MySQL. Add a read replica if you need one. You’re done.

Your write throughput fits in a single primary. Postgres on a modest EC2 instance will handle tens of thousands of writes per second. MySQL the same. If your peak write rate is under that, single-primary is fine forever.

Your team has operational expertise in these databases. This is worth actual money. A team that knows how to tune autovacuum, read EXPLAIN ANALYZE output, configure streaming replication, and recover from WAL corruption can keep Postgres humming through almost anything. That expertise doesn’t transfer to Swytch — some of the concepts do, but the operational surface is different.

You depend on Postgres or MySQL-specific features. Postgres extensions (PostGIS, pgvector, TimescaleDB, pg_partman, foreign data wrappers). MySQL’s InnoDB specifics or the storage-engine pluggability. Stored procedures, triggers with complex side effects, LISTEN/NOTIFY, logical replication. Swytch’s SQL engine is SQLite underneath, and SQLite is a different dialect with a different feature set. If your application leans on Postgres-native features, migrating is a rewrite, not a port.

You use an ORM or framework that assumes Postgres or MySQL dialect. Rails, Django, Laravel, Hibernate — they all default to one of the big two. They emit dialect-specific SQL. Swytch speaks the Postgres wire protocol, which means these frameworks will connect, but the SQL they send may hit SQLite dialect boundaries. The SQL Dialect page has specifics. This isn’t a death sentence for migration — many frameworks can be configured for SQLite.

If you’re nodding at any of these, close the tab. Postgres and MySQL are not competing with us in your specific case. They’re just the right answer.

The pattern isn’t “switch from Postgres to Swytch.” The pattern is “keep Postgres for your system of record, and add Swytch for the specific workload it’s built for.”

Two shapes where this pattern works:

A synchronized multi-region cache. Your primary Postgres is in Virginia. Your European users’ reads are slow because the latency is real. You run Swytch in Redis mode across regions as a cache layer — reads are always local, writes replicate synchronously only to the nodes subscribed to that key. Your Postgres stays the system of record; Swytch handles the read-path locality. This is the clean use case and it’s what Swytch does best.

A secondary store for data that wants to be everywhere. Some data shapes don’t want to live in a single-region primary: multi-region user-action logs, field-device writes, distributed session state, per-region operational metrics. The data needs to be writable in every region, readable locally in every region, and integrated with the rest of your system. Running Postgres for this means building out replication topology, and the topology gets ugly fast. Swytch holds the data natively — every node writes locally, reads locally, and the nodes subscribed to a given table pay only the coordination they actually need. If you have Postgres-locked reporting tools or archival workflows, you can project into Postgres on a schedule for those tools, not for consistency. Swytch’s SQL mode is serializable; the projection is just to feed whatever downstream Postgres-dialect thing you already have.

Both patterns share a shape: Postgres stays where your data lives permanently, and Swytch does what it’s actually good at — leaderless, consensus-free, serializable replication. Local reads, active-active writes, and graceful partition handling all fall out of that, for free.

If you want Swytch to replace Postgres as your system of record, the answer is: probably not yet, and probably not ever for most applications. Not because Swytch can’t do it, but because the ecosystem tradeoff isn’t worth it for workloads that don’t specifically need leaderless active-active writes with serializable guarantees.

There’s a subset of applications where Postgres or MySQL genuinely can’t serve the primary-database role:

• A global SaaS where every region needs local-write latency and a single primary is architecturally disqualified.
• A system where the read path needs to be local everywhere, and asynchronous read-replica lag isn’t acceptable for your correctness model.
• A system with nodes that go offline for hours at a time (ships, oil platforms, edge devices, spacecraft) and still need to accept writes while disconnected.

For these, the tradeoff flips. The battle-scarred Postgres playbook is less useful than it sounds, because the specific failures you’d be hitting (“the single writer region became unreachable, what do we do”) are failures Postgres doesn’t have a good answer to either. Multi-region multi-master Postgres isn’t a solved problem. It’s barely a problem anyone has solved at all, outside of some very expensive enterprise setups with a lot of asterisks. There’s a reason Cloudflare built D1 as single-primary.

If this describes your workload (and be honest about whether it does), Swytch is a legitimate choice.

Postgres and MySQL are the right default for SQL-as-system-of-record workloads, and Swytch exists to solve problems that aren’t most applications’ problem. The battle-scarred playbooks these databases come with are worth more than most architectural diagrams will ever admit, and if you can serve your workload from a single Postgres or MySQL (with or without read replicas), that’s almost certainly the right call. Swytch earns its slot when you need leaderless, consensus-free, serializable replication — and the local reads, active-active writes, and graceful partition handling that fall out of that architecture. Even then, the reasonable pattern is to run Swytch alongside your existing Postgres or MySQL, not as a replacement. Your system of record stays boring and battle-tested. Swytch handles the specific problems it was built for.