OrcaSheets
Analytics for humans, not engineers - local-first, no cloud bill
About OrcaSheets
OrcaSheets is a local-first analytics workspace built on an argument that runs against the last decade of the data industry: the compute you need for most analysis is already sitting on your desk. Rather than shipping your data to a warehouse and paying per query, OrcaSheets processes it directly on your machine, at a scale of roughly a billion rows in seconds. That removes the cloud bill, removes the latency, and removes the awkward question of whose servers your customer data is sitting on. It also works offline, which is a property that cloud analytics simply cannot offer.
The interface is designed for the person who has the question rather than the person who can write the query. You ask in plain English and OrcaSheets turns it into a SQL query that you can read, edit and rerun, which matters because it makes the tool auditable instead of magical. When you do want SQL, you write SQL. Connectivity covers more than twenty sources across warehouses such as Snowflake and Databricks, databases including PostgreSQL, MySQL and MongoDB, and flat files in CSV, Parquet and JSON. The local-first architecture means no servers, no shadow copies and no background tracking, with every calculation staying under your control. A Mac app is distributed through Setapp, and the platform has been shown publicly on Hacker News and Product Hunt.
Install OrcaSheets on your machine and connect your sources, whether that is a production Postgres replica, a Snowflake warehouse or a folder of Parquet files. Ask a question the way you would ask a colleague, and read the SQL that OrcaSheets generates in response before you trust the number. Edit that query if the interpretation was slightly off, rerun it, and keep going. Build the results into dashboards for the work you repeat, such as month-end close, reconciliations or cohort analysis. Because processing happens locally, iteration is immediate and there is no per-query cost to discourage you from exploring. Paid tiers add a fourteen-day trial before you commit.
- •Plain English to Readable SQL - Questions are translated into SQL you can actually read, edit and rerun, so results stay auditable rather than arriving as an unexplained number
- •Local Processing at Scale - Handles up to a billion rows directly on your own hardware in seconds, with no warehouse spin-up and no per-query billing
- •20+ Data Connectors - Snowflake, Databricks, PostgreSQL, MySQL and MongoDB alongside CSV, Parquet and JSON files
- •No Cloud Dependency - No servers, no shadow copies and no background tracking; the tool works fully offline and data never leaves your machine
- •Dashboards - Build reusable views for recurring work such as month-end close, reconciliations, inventory tracking and campaign reporting
- •Flat Team Pricing - Team plans are a flat monthly fee with no per-seat charges, so adding an analyst does not change the bill
- •Native Mac App - Distributed through Setapp as a desktop application rather than a browser tab
Fits finance and operations teams doing month-end close, reconciliations and inventory tracking who currently wait on a data team for every question, growth teams running cohort, funnel and campaign performance analysis, and small companies that want real analytics without a warehouse contract. It is a strong fit for organisations handling regulated or otherwise sensitive data where the local-first guarantee removes an entire compliance conversation. Analysts who can write SQL benefit too, since the plain-English layer produces a starting query rather than replacing their judgement.
Pricing
$0 - $100/mo
Free Forever for one user with 150 AI questions a month. Professional $10/month for one user. Small Teams $100/month per org for up to 10 users, billed per organisation rather than per seat. Scale and Enterprise is contact-only.
Checked 2026-09-22
