Spreadsheets · head to head
Rowy vs StarRocks

Rowy
Spreadsheets
Spreadsheet interface for Google Cloud Firestore with cloud functions written in the browser
- From
- Free
- Rated
- -

StarRocks
Databases
Apache 2.0 MPP analytical database built for joins on open table formats
- From
- Free
- Rated
- -
The short version
- Each has a real cost: 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.; StarRocks self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.
- They diverge on capability: Rowy covers Firestore backed grid, StarRocks covers Cost-based optimiser.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which Rowy and StarRocks actually diverge.
Identical on both: starting price (Free), pricing model (Open source, no licence fee), 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 Rowy
- Firestore backed grid
- Browser authored cloud functions
- Typed columns
- Runs in your Google Cloud project
- Role based access
- Form view
- Open source
Only in StarRocks
- Cost-based optimiser
- Lakehouse query engine
- Primary key tables
- Materialised views
- Shared-data mode
- MySQL wire protocol
What people use each for
The jobs each tool is most often brought in to do.
Rowy
- A Firebase application that needs an internal admin interface without building onenot StarRocks
- Operations staff correcting production records in Firestore without developer involvementnot StarRocks
- Attaching a small transformation or notification function to a field change without a full deployment pipelinenot StarRocks
- A content team populating documents that a mobile application reads directly from Firestorenot StarRocks
StarRocks
- Customer-facing analytics where queries join a fact table to several dimensions and must return in well under a secondnot Rowy
- Querying an Iceberg lakehouse directly without copying data into a proprietary warehouse formatnot Rowy
- Replacing a ClickHouse deployment that has become unmanageable because every new question needs another denormalised tablenot Rowy
- Real-time analytics fed by change data capture where rows must be updated in place rather than appendednot Rowy
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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.
StarRocks
- Self-hosting is a genuine operations job: frontend and backend node roles, tablet distribution, compaction and materialised view refresh all need an owner, and there is no small-team-friendly single-binary mode.
- CelerData is by far the dominant contributor despite Linux Foundation stewardship, so the practical roadmap risk is the same as any single-vendor open source project.
- It inherits a MySQL-flavoured SQL dialect from its Doris ancestry, so queries written for PostgreSQL, Snowflake or Trino need rewriting rather than porting.
- Ecosystem support is thinner than ClickHouse or Trino: fewer client libraries, fewer managed hosting options and a much smaller pool of engineers who have run it in production.
- Memory pressure under concurrent large joins is a common production failure, and the tuning knobs for query memory limits are unforgiving compared with a cloud warehouse that just scales.
Pricing, plan by plan
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
StarRocks
Free- StarRocksFree
- Apache 2.0 licence
- Linux Foundation governance
- No usage or node limits
- CelerData Cloud$undefined/year
- Managed StarRocks from the primary contributor
- BYOC and serverless deployment options
- Enterprise support and SLAs
Which should you pick?
Choose Rowy if
- You need firestore backed grid.
- You want to start without paying.
- You also want browser authored cloud functions.
Choose StarRocks if
- You need cost-based optimiser.
- You want to start without paying.
- You work on Linux, Docker, Kubernetes.
- You also want lakehouse query engine.
Questions people ask
- Is Rowy or StarRocks better?
- Neither clearly leads. Rowy starts at Free and StarRocks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Rowy or StarRocks?
- Rowy starts at Free and StarRocks at Free.
- Does Rowy or StarRocks run on more platforms?
- Rowy runs on Web. StarRocks runs on Linux, Docker, Kubernetes.
- Can I use Rowy for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Rowy best used for?
- Rowy is most often used for a firebase application that needs an internal admin interface without building one, operations staff correcting production records in firestore without developer involvement, attaching a small transformation or notification function to a field change without a full deployment pipeline, a content team populating documents that a mobile application reads directly from firestore. Of those, a firebase application that needs an internal admin interface without building one and operations staff correcting production records in firestore without developer involvement are not what StarRocks is typically brought in for.
- What can Rowy do that StarRocks cannot?
- Rowy covers Firestore backed grid, Browser authored cloud functions, Typed columns, Runs in your Google Cloud project. StarRocks covers Cost-based optimiser, Lakehouse query engine, Primary key tables, Materialised views.
Answered from the vendors’ own pages
Rowy: Where is my data stored?
In your own Firestore instance inside your own Google Cloud project. Rowy does not hold a copy.
StarRocks: Is StarRocks open source?
Yes, Apache 2.0, governed under the Linux Foundation since 2023.
Rowy: 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.
StarRocks: How does it differ from ClickHouse?
StarRocks is built for joins across a star schema with a cost-based optimiser; ClickHouse is fastest on denormalised single tables.
Rowy: Can it do joins across collections?
Not really. Firestore does not support joins, and no interface layer can add them.
StarRocks: Who maintains it?
CelerData, formerly StarRocks Inc, is the dominant contributor and sells the managed service.
Rowy: Is there a row limit?
Not from Rowy. The limits that bite are Firestore document size and per document write throughput.
StarRocks: Can it query Iceberg tables directly?
Yes, along with Hudi, Delta Lake, Hive and Paimon, with a local cache for repeat queries.
Rowy: Is it suitable if I am not on Firebase?
No. It is specifically a Firestore interface.
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- StarRocks vs Cube Software
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- StarRocks vs Apache Druid
- StarRocks vs Presto
- StarRocks vs DuckDB
- StarRocks vs Dremio
- StarRocks vs Aiven
- StarRocks vs Typesense
- StarRocks vs VerneMQ
- StarRocks vs PostgreSQL
- StarRocks vs RabbitMQ
- StarRocks vs Vitess
- StarRocks vs BigQuery
- StarRocks vs CosmosDB
- StarRocks vs DataStax
- StarRocks vs dbt
- StarRocks vs Apache Doris
- StarRocks vs Apache Kafka
