Machine Learning · head to head
Ray vs Rowy
Rowy
Spreadsheets
Spreadsheet interface for Google Cloud Firestore with cloud functions written in the browser
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Ray windows support is beta and multi node Ray clusters are untested on Windows; Rowy every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
- They diverge on capability: Ray covers Distributed computing, Rowy covers Firestore backed grid.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Ray and Rowy actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
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 Ray
- Distributed computing
- Ray Train
- Ray Tune
- RLlib
- Ray Serve
- PyTorch
- TensorFlow
- Hugging Face
Only in Rowy
- Firestore backed grid
- Browser authored cloud functions
- Typed columns
- Runs in your Google Cloud project
- Role based access
- Form view
- Open source
What people use each for
The jobs each tool is most often brought in to do.
Ray
- Distributed AI model training and servingnot Rowy
- Large-scale data processingnot Rowy
- Reinforcement learning workloadsnot Rowy
- ML inference servingnot Rowy
Rowy
- A Firebase application that needs an internal admin interface without building onenot Ray
- Operations staff correcting production records in Firestore without developer involvementnot Ray
- Attaching a small transformation or notification function to a field change without a full deployment pipelinenot Ray
- A content team populating documents that a mobile application reads directly from Firestorenot Ray
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Ray
- Windows support is beta and multi node Ray clusters are untested on Windows
- Windows lacks copy on write forking, which raises memory requirements, and Ray code assumes UNIX filenames
- Multi node clusters are untested on Apple Silicon Macs
- The Java API is experimental and community supported only, and requires matching Java and Python versions
- Python 3.13 support is beta
Rowy
- Every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
- Firestore has no joins, so linking tables in the grid is a convenience layer rather than a relational feature and reports across collections still need a separate query.
- It is useful only to teams already on Firebase, so choosing it effectively locks the operational tooling to one cloud vendor.
- Query costs are billed by document read, and an unfiltered grid on a large collection can generate a bill that a spreadsheet user has no intuition for.
- Development activity has slowed relative to the broader category, so evaluate current maintenance before making it load bearing for internal operations.
Pricing, plan by plan
Ray
Free- Open SourceFree
- Full Ray framework
- All libraries
- Community support
- Anyscale PlatformFree
- Managed infrastructure
- Enterprise support
- SLAs
Rowy
Free- Open source self hostedFree
- No licence fee
- Deploys into your own Google Cloud project
- You pay Google Cloud for Firestore reads, writes and storage
Which should you pick?
Choose Ray if
- You need distributed computing.
- You want to start without paying.
- You work on Linux, Mac, Windows.
- You also want ray train.
Choose Rowy if
- You need firestore backed grid.
- You want to start without paying.
- You also want browser authored cloud functions.
Questions people ask
- Is Ray or Rowy better?
- Neither clearly leads. Ray starts at Free and Rowy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Ray or Rowy?
- Ray starts at Free and Rowy at Free.
- Does Ray or Rowy run on more platforms?
- Ray runs on Linux, Mac, Windows. Rowy runs on Web.
- Can I use Ray for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Ray best used for?
- Ray is most often used for distributed ai model training and serving, large-scale data processing, reinforcement learning workloads, ml inference serving. Of those, distributed ai model training and serving and large-scale data processing are not what Rowy is typically brought in for.
- What can Ray do that Rowy cannot?
- Ray covers Distributed computing, Ray Train, Ray Tune, RLlib. Rowy covers Firestore backed grid, Browser authored cloud functions, Typed columns, Runs in your Google Cloud project.
Answered from the vendors’ own pages
Ray: Is Ray free?
Yes. Ray is free and open source software with over 34,800 GitHub stars and 1,000+ contributors. Users can download and use the Ray framework at no cost.
SourceRowy: Where is my data stored?
In your own Firestore instance inside your own Google Cloud project. Rowy does not hold a copy.
Ray: Is there a paid option for Ray?
Yes. Anyscale, the managed platform built by Ray's creators, offers paid tiers with enterprise features like governance and advanced tooling. Specific Anyscale pricing details are not listed on the Ray website.
SourceRowy: What does it cost to run?
No licence fee. You pay Google Cloud for Firestore reads, writes, storage and function invocations, and an open grid on a big collection reads a lot.
Ray: Can I try Ray with credits?
Yes. New users can try Ray with $100 credit on Anyscale's managed platform to explore the service.
SourceRowy: Can it do joins across collections?
Not really. Firestore does not support joins, and no interface layer can add them.
Rowy: Is there a row limit?
Not from Rowy. The limits that bite are Firestore document size and per document write throughput.
Rowy: Is it suitable if I am not on Firebase?
No. It is specifically a Firestore interface.
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