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Databases · head to head

Tinybird vs Valkey

Tinybird logo

Tinybird

Databases

Managed ClickHouse with a workflow that turns SQL queries into hosted HTTP APIs

From
Free
Rated
-
Full reviewWebsite
Valkey logo

Valkey

Databases

Open-source in-memory data store forked from Redis

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Tinybird it is ClickHouse underneath, so it inherits ClickHouse limits: multi-table joins degrade badly at scale, updates and deletes are expensive mutations rather than cheap operations, and a poorly chosen sorting key at table creation cannot be fixed without rebuilding the data.; Valkey younger project, so its track record is short even though the codebase is not
  • They diverge on capability: Tinybird covers Managed ClickHouse, Valkey covers Redis-compatible.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Tinybird and Valkey actually diverge.

Attributes where Tinybird and Valkey differ
AttributeTinybirdValkey
Pricing modelPer month by compute and storageOpen source, no licence fee; managed cloud billed separately
PlatformsWeb, Cloud, Linux, macOSLinux, macOS, Docker, Self-hosted

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Databases).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Tinybird

  • Managed ClickHouse
  • Pipes as APIs
  • Events HTTP endpoint
  • Streaming connectors
  • Materialized views
  • Git-based workflow
  • Token-scoped auth
  • Observability

Only in Valkey

  • Redis-compatible
  • BSD licensed
  • Rich data structures
  • Replication and persistence

What people use each for

The jobs each tool is most often brought in to do.

Tinybird

  • A SaaS product adding a per-customer usage dashboard that must render in under a second across billions of eventsnot Valkey
  • A team building rate limiting or fraud checks that need an aggregate over the last few minutes returned inside a request cyclenot Valkey
  • A data team offloading interactive operational dashboards from Snowflake, where per-query warehouse cost makes constant refresh untenablenot Valkey
  • A game or ad-tech company ingesting a high-volume event stream and exposing live counters back to customers through an APInot Valkey

Valkey

  • Continuing on a permissively licensed in-memory store after the Redis licence changenot Tinybird
  • Caching and session storage where a foundation-governed project is a procurement requirementnot Tinybird
  • Migrating from Redis without rewriting application codenot Tinybird

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Tinybird

  • It is ClickHouse underneath, so it inherits ClickHouse limits: multi-table joins degrade badly at scale, updates and deletes are expensive mutations rather than cheap operations, and a poorly chosen sorting key at table creation cannot be fixed without rebuilding the data.
  • Compute is metered per vCPU-second with overage at 0.0002 USD per second, so an inefficient query shipped to production shows up directly on the invoice rather than merely running slowly.
  • Only the Enterprise tier gets horizontal scaling and dedicated infrastructure; Free, Developer and SaaS all run on shared infrastructure with vertical scaling only, which caps both isolation and headroom for anyone not on a custom contract.
  • Storage is billed at 0.058 USD per gigabyte on top of compute, and egress is charged separately at 0.01 USD per gigabyte intra-cloud and 0.10 USD inter-cloud, so a high-fanout API serving many small responses accrues costs in three places at once.
  • You are building on a proprietary workflow around an open database: the pipes, tokens and API layer are Tinybird specific, so leaving means keeping your data but rewriting the entire serving layer you adopted Tinybird to avoid writing.

Valkey

  • Younger project, so its track record is short even though the codebase is not
  • Divergence from Redis grows over time, so compatibility is strongest near the fork point and weakens as both evolve
  • Ecosystem tooling and documentation still frequently assume Redis, leaving translation work

Pricing, plan by plan

Tinybird

Free
  • FreeFree
    • 0.25 vCPU on shared infrastructure
    • 10 GB storage included
    • 1,000 requests per day
  • Developer$25/month
    • 0.5 vCPU scaling to 8 vCPU
    • 25 GB storage included
    • Two replicas
  • SaaS$undefined/month
    • Up to 32 vCPU
    • 500 GB storage included
    • Four to sixteen threads per request
  • Enterprise$undefined/year
    • Unlimited vCPU and bottomless storage
    • Dedicated infrastructure and private regions
    • Vertical and horizontal scaling

Valkey

Free
  • ValkeyFree
    • Full functionality
    • Self-hosted
    • No usage limits

Which should you pick?

Choose Tinybird if

  • You need managed clickhouse.
  • You want to start without paying.
  • You work on Web, Cloud, Linux, macOS.
  • You also want pipes as apis.
Tinybird review

Choose Valkey if

  • You need redis-compatible.
  • You want to start without paying.
  • You work on Linux, macOS, Docker, Self-hosted.
  • You also want bsd licensed.
Valkey review

Questions people ask

Is Tinybird or Valkey better?
Neither clearly leads. Tinybird starts at Free and Valkey at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Tinybird or Valkey?
Tinybird starts at Free and Valkey at Free.
Does Tinybird or Valkey run on more platforms?
Tinybird runs on Web, Cloud, Linux, macOS. Valkey runs on Linux, macOS, Docker, Self-hosted.
Can I use Tinybird for free?
Both have a free tier, so you can try either at no cost before committing.
What is Tinybird best used for?
Tinybird is most often used for a saas product adding a per-customer usage dashboard that must render in under a second across billions of events, a team building rate limiting or fraud checks that need an aggregate over the last few minutes returned inside a request cycle, a data team offloading interactive operational dashboards from snowflake, where per-query warehouse cost makes constant refresh untenable, a game or ad-tech company ingesting a high-volume event stream and exposing live counters back to customers through an api. Of those, a saas product adding a per-customer usage dashboard that must render in under a second across billions of events and a team building rate limiting or fraud checks that need an aggregate over the last few minutes returned inside a request cycle are not what Valkey is typically brought in for.
What can Tinybird do that Valkey cannot?
Tinybird covers Managed ClickHouse, Pipes as APIs, Events HTTP endpoint, Streaming connectors. Valkey covers Redis-compatible, BSD licensed, Rich data structures, Replication and persistence.

Answered from the vendors’ own pages

Tinybird: Is Tinybird just hosted ClickHouse?

No. The database is ClickHouse, but the product is the layer above it: publishing parameterised SQL as authenticated, rate-limited REST endpoints without writing an API server.

Valkey: Is Valkey free?

Yes, BSD-licensed open source under the Linux Foundation.

Tinybird: What does it actually cost?

Free tier at 1,000 requests a day, Developer from 25 USD a month, then compute at 0.0002 USD per vCPU-second and storage at 0.058 USD per gigabyte. Higher tiers are quoted.

Valkey: Why does Valkey exist?

Redis changed its licence away from BSD in 2024. Valkey is the community fork continuing under permissive terms, backed by AWS, Google Cloud and Oracle among others.

Tinybird: Can I run it on my own infrastructure?

Only on Enterprise, which offers dedicated infrastructure and private regions. Lower tiers are shared multi-tenant cloud.

Valkey: Can I switch from Redis to Valkey?

At the fork point it is drop-in compatible with existing clients and data. The further both projects move from that point, the more you should verify the specific features you use.

Tinybird: Does it handle updates and deletes?

Poorly, as ClickHouse does. Design for append-only event data; frequent mutation is the wrong workload for this engine.

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