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The best Aiven alternatives in 2026

Ajay Kumar··9 min read

Aiven's pitch is breadth: managed Postgres, MySQL, Kafka, ClickHouse, OpenSearch, Valkey and Flink, on the cloud and region of your choosing, behind one console and one bill. If you genuinely run four of those, it's a good deal — the operational surface you're outsourcing is enormous.

The teams that end up searching for alternatives are usually the other kind: they came for Postgres, they still only use Postgres, and they're paying platform-shaped prices for a single database. Below is how I'd think about the move. I build PandaStack, which is one of the options, so treat that section with the appropriate suspicion and read the rest for the reasoning.

Work out what you're actually leaving behind

Before comparing anything, write down which Aiven features are load-bearing for you. In practice it's a short list, and it's never the same list twice:

  • Multi-cloud and region choice — real if you have a data-residency commitment, decorative if you don't.
  • Read replicas and cross-region replication — check whether you use them or just enabled them once.
  • Point-in-time recovery and backup retention — almost always load-bearing, and the thing people forget to verify on the new platform.
  • VPC peering / PrivateLink — load-bearing for enterprise networks, irrelevant if your app talks to the database over TLS from a managed host.
  • The non-Postgres services — if Kafka is in production, most of this post doesn't apply to you.
  • SOC 2 / ISO paperwork your customers ask for.

The migration itself is rarely the hard part. Postgres is Postgres, pg_dump and logical replication both work, and a well-planned cutover costs you a few seconds of write downtime. What bites people is discovering on day three that the new platform's PITR window is 24 hours when they'd been assuming seven days.

Neon — for branch-per-preview workflows

Neon separates storage from compute and gives you database branching that feels like Git. Branches are cheap, they're the whole point, and if your team wants a database per pull request without writing seeding scripts, that's a genuine reason to pick it.

The trade is architectural. Compute scales to zero, which is great for cost and means an idle branch can take a moment to wake on the next connection. You're also on Neon's storage engine rather than vanilla Postgres on a disk — mostly invisible, occasionally relevant if you depend on an extension they don't ship. Check your extension list before you commit to anything, on any platform in this post.

Amazon RDS and Aurora — for when the answer is 'whatever AWS says'

If your infrastructure already lives in AWS, RDS removes a vendor rather than adding one, and it puts the database inside the VPC your application is already in. Aurora goes further on the storage layer and gets you faster failover and cheaper read replicas at the cost of being further from stock Postgres.

What you give up versus Aiven is the console-driven simplicity. RDS assumes you're comfortable with parameter groups, subnet groups, IAM, and a maintenance-window model where an unattended minor upgrade can restart your primary at 3am. That's not a criticism — it's an accurate description of the audience.

Supabase — when the database is the backend

Supabase is Postgres plus the things people build on top of Postgres: auth, row-level-security-driven APIs, storage, realtime. If you're building a product where the client talks to the database more or less directly, this collapses a lot of code.

It's the wrong shape if you have a conventional application server and just want a database — you'd be adopting a platform's opinions about auth and API generation in exchange for nothing you need.

Self-hosting — cheaper than everyone, until it isn't

Postgres on a VM you rent is dramatically cheaper per gigabyte than every managed option, and for a side project or an internal tool it's a completely reasonable answer. The honest accounting includes backups you've tested restoring, minor version upgrades, connection limits, disk-full alerts, and someone's phone number at 3am.

The self-hosting decision hinges on one question: have you ever restored one of your backups? If the answer is no, you don't have backups, you have files. Test the restore before you rely on the setup, not after.

PandaStack — Postgres next to the thing that queries it

This is the one I build, so here's the specific shape rather than a sales pitch. Each managed database is a Firecracker microVM with its own kernel and a durable volume — hardware-level isolation between tenants, not a shared cluster with schema separation. You get stock Postgres 16 with the extensions people actually use already installed: pgvector, pg_stat_statements, pg_trgm, pgcrypto, uuid-ossp, ltree, hstore, unaccent.

curl -X POST https://api.pandastack.ai/v1/databases \
  -H "Authorization: Bearer $PANDASTACK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"label":"production","size":"4g"}'

# Returns a connection URL you can hand straight to your app:
# postgres://pandastack:<pw>@<id>.db.pandastack.ai:5432/pandastack?sslmode=require

Three things are different from the platforms above. Branching clones a database into a new one from its archive, including point-in-time targets, so you can rehearse a migration against real data and throw the copy away. Idle databases suspend and bill storage only, then wake on connection. And apps deployed on the same platform sit beside the database rather than across the internet from it.

What it isn't: a multi-service data platform. There's no managed Kafka, no OpenSearch, no ClickHouse. If your Aiven bill is mostly non-Postgres services, this is not the move.

Choosing, in four lines

  1. You run Kafka or OpenSearch in production — stay on Aiven, or split them out deliberately and accept two vendors.
  2. You're already deep in AWS and have a platform team — RDS or Aurora.
  3. Your workflow is branch-per-PR and your app is serverless — Neon.
  4. You want Postgres and the app that queries it on the same platform, with isolation you can explain to a security reviewer — PandaStack.

The migration, briefly

For anything under a few hundred gigabytes with a tolerable maintenance window, a dump and restore is the boring, reliable answer:

# Dump from Aiven (schema + data, custom format so you can restore in parallel)
pg_dump --format=custom --no-owner --no-acl \
  "postgres://avnadmin:<pw>@<host>:<port>/defaultdb?sslmode=require" \
  --file=dump.pgc

# Restore into the new database
pg_restore --no-owner --no-acl --jobs=4 \
  --dbname="postgres://pandastack:<pw>@<id>.db.pandastack.ai:5432/pandastack?sslmode=require" \
  dump.pgc

If your downtime budget is measured in seconds rather than minutes, use logical replication instead: create a publication on the old database, subscribe from the new one, let it catch up, then flip the application's connection string during a brief write pause. The details are in the migration guide linked below.

Whichever platform you choose, verify three things on day one: the PITR window in hours, whether the connection string you're given is pooled or direct, and that every extension in `SELECT extname FROM pg_extension` on the old database exists on the new one.

Frequently asked questions

Is Aiven expensive compared to the alternatives?

It's priced as a multi-service data platform, which is the right price if you use it as one. The teams who find it expensive are almost always running a single Postgres instance on it, where the per-month cost sits well above single-purpose managed Postgres providers for equivalent memory. Before switching on price alone, add up what you'd pay across the replacements — if you'd need a second vendor for Kafka and a third for search, the consolidated bill can come out ahead.

Can I move off Aiven without downtime?

Close to it. Logical replication lets the new database follow the old one until it's caught up, so the actual cutover is a brief pause on writes while you switch the connection string — typically seconds. A pg_dump and pg_restore is simpler but takes the database offline for the length of the restore, which scales with data size and index count. The one thing neither approach handles for you is extensions: check them first, because a restore that fails on a missing extension halfway through is the worst version of this migration.

Do I lose point-in-time recovery if I leave Aiven?

Not necessarily, but the retention window varies a lot and it's the detail people skip. Ask for the specific window in hours or days, whether the recovery target can be an arbitrary timestamp or only a backup boundary, and whether restoring creates a new instance or overwrites the existing one. On PandaStack, a point-in-time restore clones into a brand-new database from the archive, so the source is untouched and you can compare the two before switching anything.

What about self-hosting Postgres on a cheap VM?

Financially it wins by a wide margin, and for internal tools it's genuinely the right call. The costs that don't appear on the invoice are backup verification, minor and major version upgrades, disk growth monitoring, and the incident response you now own. A reasonable middle path is self-hosting anything whose loss would be annoying, and paying for managed Postgres for anything whose loss would be a phone call from a customer.

Does moving to a managed provider mean I can't use my Postgres extensions?

It means you have to check. Every managed provider ships an allowlist, and it differs. Run SELECT extname FROM pg_extension on your current database and compare it against the new provider's list before you plan anything else. The common ones — pgvector, pg_stat_statements, pg_trgm, pgcrypto, uuid-ossp, hstore — are widely available; anything requiring a custom C extension or superuser almost never is.

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Written by Ajay Kumar, Founder, PandaStack.