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Developer Tools · head to head

Ona (formerly Gitpod) vs Tinybird

Ona (formerly Gitpod) logo

Ona (formerly Gitpod)

Developer Tools

Cloud development environments repositioned as a control plane for software engineering agents

From
Free
Free plan
Yes
Tinybird logo

Tinybird

Databases

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

From
Free
Free plan
Yes

The short version

  • Free plans on both; paid from $20/mo and $25/mo.
  • Only Ona (formerly Gitpod) lists ephemeral environments; only Tinybird lists managed ClickHouse.
  • Prices and features on this page were last checked on 31 August 2026.

Where they differ

Only the attributes on which Ona (formerly Gitpod) and Tinybird actually diverge.

Attributes where Ona (formerly Gitpod) and Tinybird differ
AttributeOna (formerly Gitpod)Tinybird
Pricing modelPer month by compute unitPer month by compute and storage
PlatformsWeb, Linux, macOS, Windows, AWSWeb, Linux, macOS
CategoryDeveloper ToolsDatabases

Identical on both: starting price (Free), free tier (Yes).

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 Ona (formerly Gitpod)

  • Ephemeral environments
  • Agent sessions
  • Bring your own cloud
  • Devcontainer standard
  • Compute unit budgeting
  • Enterprise identity

Only in Tinybird

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

What people use each for

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

Ona (formerly Gitpod)

  • Giving a large engineering team identical, disposable environments so onboarding is a link rather than a two day setupnot Tinybird
  • Running several coding agents in parallel against real databases and services instead of on a laptopnot Tinybird
  • Keeping source code off contractor and offshore laptops by moving the whole environment into a controlled accountnot Tinybird
  • Reproducing a hard-to-configure toolchain for a short-lived project without polluting anyone machinenot Tinybird

Tinybird

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

Where each one falls short

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

Ona (formerly Gitpod)

  • Acquisition risk has already materialised: the company closed a sale to OpenAI on 10 August 2026 and now sits inside the Codex team, so nothing public guarantees pricing, continuity or neutrality between model vendors beyond honouring existing commitments
  • Two disruptive changes of direction inside a year, from development environments to agent orchestration and then from independence to acquisition, mean the product a browser IDE buyer originally chose no longer exists in that form
  • The Gitpod Classic sunset on 15 October 2025 required manual conversion of configuration, hand-moved secrets, self-rescued workspace data and a brand new account, which is the clearest available precedent for how the vendor handles deprecation
  • Community self-hosting is finished: the AGPL-3.0 repository is deprecated by its own README, and self-hosted now means a vendor-operated install in your AWS or GCP account, with no Azure, no on-premises and no air-gapped path
  • Pricing is difficult to model because it runs on a compute unit currency where subscription credits expire at the end of the month, the mapping from units to actual compute is not published on the pricing page, and Enterprise is quotation only

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

Pricing, plan by plan

Ona (formerly Gitpod)

Free
  • FreeFree
    • Up to 3 parallel environments
    • Machines up to 4 vCPU, 16 GB memory and 80 GB disk
    • Ona Cloud multi-tenant only
  • Core$20/mo
    • From 20 US dollars a month, up to 100 team members
    • Includes 80 to 2,200 recurring compute units a month depending on tier
    • Additional units from 10 US dollars per 40 units
  • EnterpriseOn request
    • Single-tenant deployment in your own AWS or GCP account
    • SAML and OIDC single sign-on
    • Dedicated account management and forward deployed engineers

Tinybird

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

Which should you pick?

Choose Ona (formerly Gitpod) if

  • You need ephemeral environments.
  • You want to start without paying.
  • You work on Web, Linux, macOS, Windows, AWS.
  • You also want agent sessions.

Choose Tinybird if

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

Questions people ask

Is Ona (formerly Gitpod) or Tinybird better?
Neither clearly leads. Ona (formerly Gitpod) starts at Free and Tinybird at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Ona (formerly Gitpod) or Tinybird?
Ona (formerly Gitpod) starts at Free and Tinybird at Free.
Does Ona (formerly Gitpod) or Tinybird run on more platforms?
Ona (formerly Gitpod) runs on Web, Linux, macOS, Windows, AWS. Tinybird runs on Web, Linux, macOS.
Can I use Ona (formerly Gitpod) for free?
Both have a free tier, so you can try either at no cost before committing.
What is Ona (formerly Gitpod) best used for?
Ona (formerly Gitpod) is most often used for giving a large engineering team identical, disposable environments so onboarding is a link rather than a two day setup, running several coding agents in parallel against real databases and services instead of on a laptop, keeping source code off contractor and offshore laptops by moving the whole environment into a controlled account, reproducing a hard-to-configure toolchain for a short-lived project without polluting anyone machine. Of those, giving a large engineering team identical, disposable environments so onboarding is a link rather than a two day setup and running several coding agents in parallel against real databases and services instead of on a laptop are not what Tinybird is typically brought in for.
What can Ona (formerly Gitpod) do that Tinybird cannot?
Ona (formerly Gitpod) covers Ephemeral environments, Agent sessions, Bring your own cloud, Devcontainer standard. Tinybird covers Managed ClickHouse, Pipes as APIs, Events HTTP endpoint, Streaming connectors.

Answered from the vendors’ own pages

Ona (formerly Gitpod): Is Gitpod still called Gitpod?

No. It rebranded to Ona in September 2025, and gitpod.io now redirects to ona.com. The company was acquired by OpenAI in a deal that closed on 10 August 2026.

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.

Ona (formerly Gitpod): Can I still self-host it for free?

No. The AGPL-3.0 self-hosted project is deprecated by its own README. What is offered now is a vendor-operated single-tenant install in your AWS or GCP account on the Enterprise plan.

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.

Ona (formerly Gitpod): What happened to Gitpod Classic?

Pay-as-you-go Classic was switched off on 15 October 2025. Migration required converting gitpod.yml to devcontainer.json, moving secrets by hand, downloading workspace data before the cutoff and creating a new account.

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.

Ona (formerly Gitpod): What does it cost?

Core starts at 20 US dollars a month and includes a monthly allowance of Ona Compute Units, with more from 10 dollars per 40 units. Subscription credits expire monthly. Enterprise is quoted.

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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