DatronomeQuestions and answers
Plain answers about what Datronome does, how it compares, and what it costs.
What is Datronome?
What is Datronome?
Datronome is a decision-operations tool: it turns recurring data work into pipelines that run on a schedule, checks the data before anything downstream runs, routes decisions to a person for approval, and records every decision with its outcome. It runs on your own Windows machine or server, and your data stays there unless you connect a cloud assistant or another service you choose.
Who is Datronome for?
Analysts, operations teams and small data teams who run recurring reports and decisions today with SQL, Excel, Python scripts and email. It is designed for people who can write a query or a short script but do not want to run infrastructure. It is not built for platform engineering teams that need a distributed orchestrator.
Is Datronome a data pipeline tool or a decision tool?
Both, in that order. The pipeline part (SQL, Python, commands, API calls, mailboxes, quality checks) gets the data ready. The decision part (approval steps with the data in front of the approver, a decision log, outcome checks, a hit rate) is what makes it different from an orchestrator.
Does my data leave my machine?
Not unless you choose to send it. Datronome runs on your own computer or server. The only outbound connections are the ones your tasks make (your warehouse, an API you call) and, if you switch them on, email or Teams alerts and the AI assistant. A cloud assistant (Hugging Face or Anthropic) sees pipeline code, column names and run logs; a local model keeps even that inside your network.
Airflow, Alteryx and other tools
Is Datronome an Apache Airflow alternative?
For analysts and small teams, yes. Datronome installs on Windows in minutes with one file, needs no Docker or Kubernetes, and has a visual builder instead of Python DAG files. It is not a replacement for Airflow at platform scale: it runs on one machine without distributed workers, so large engineering teams should keep Airflow, Prefect or Dagster.
Airflow 2 reached end of life in 2026. Should I migrate to Datronome?
If your Airflow mostly runs a handful of scheduled SQL and Python jobs for an analytics team, migrating is a day's work and you gain quality checks, approvals and a decision log. If you have hundreds of DAGs, backfills and Kubernetes workers, upgrade to Airflow 3 instead; Datronome is not built for that scale.
Is Datronome an Alteryx alternative?
For scheduled data work, yes, at a fraction of the price: Datronome has one flat price per company instead of a price per person, and the Starter plan is free. Alteryx has hundreds of drag-and-drop transforms; Datronome expects you to write the transform in SQL or Python and gives you the scheduling, checks, approvals and decision tracking around it.
How is Datronome different from Mage, Prefect or Dagster?
Those are orchestrators for engineers who write pipelines as code. Datronome is for the person who receives the pipeline's output and has to decide something with it: it adds approval steps, a decision log with outcomes, and receipts. It also runs on Windows without containers, which none of the three do natively.
Can Datronome replace dbt?
Not yet. Datronome runs SQL on a schedule with quality checks, but it does not have dbt's model graph, ref() lineage or incremental models. A dbt-style modeling layer is on the roadmap; today, teams that use dbt keep it and use Datronome for the scheduling, checks and decisions around it.
Can Datronome replace Excel for planning?
It replaces the fragile parts: the manual refresh, the copy-paste, the formula nobody understands, and the knowledge that lives in one person's head. It keeps Excel as the front end: upload .xlsx files as inputs and download any result as an Excel workbook.
What it does
What kinds of tasks can a Datronome pipeline run?
SQL against your warehouse (SQLite, Postgres, SQL Server, MySQL, Snowflake, BigQuery, Databricks), Python, Windows or shell commands, API calls, reading a mailbox, moving files, quality checks, predictions with a trained model, optimization, and approval steps.
How do data quality checks work?
A quality-check task is a list of plain rules: rows >= 1, not_null: account_id, unique: invoice_id, range: amount 0 50000, allowed: region NA, EMEA, anomaly: amount. If a rule fails, the pipeline stops there and, if alerts are on, a person gets an email or Teams message with the failing rule.
What is an approval step?
The pipeline pauses, the request appears in an inbox with the actual data table, and a named person approves or rejects with a comment. Rejection stops the pipeline; a time limit expires the request. Every decision is recorded with who, when, on what data, and a dollar value if you set one.
What is a decision receipt?
A downloadable record of one decision: the table the approver saw, who decided, when, their comment, the value at stake, and what happened afterwards. It includes a SHA-256 checksum of the receipt, so any later change to the downloaded file shows up when the checksum is recomputed. It is not proof against someone who can edit the Datronome database itself.
How does outcome tracking work?
An approval step can name a follow-up pipeline and a rule. That many days after approval, Datronome runs the pipeline and judges the decision (for example, it worked if sla_breaches.csv has zero rows). The decision log then shows a hit rate: what share of your team's approved decisions actually worked.
Can Datronome train machine-learning models?
Yes, for tabular data. A Predict task learns from a CSV, holds out 20% to score honestly, tries linear and boosted-tree models, keeps the better one, and saves it with its scores. A second Predict task scores new rows. It is built for analysts; a data science team with custom feature engineering will still want their own tooling.
Can Datronome optimize allocations or schedules?
Yes. An Optimize task makes one decision per row under limits written in plain lines (maximize: value, total <= 10000, budget: cost <= 250000, each <= capacity, group region total <= 4000) and reports which limits held the answer back.
Does Datronome have an AI assistant?
Yes. It reads your pipelines and run logs, explains failures, and drafts or fixes tasks as proposals you apply with a button. It runs on Hugging Face (the default: paste one free token), Anthropic's API, or a local model (Ollama, vLLM, LM Studio) so nothing has to leave your network.
Installing and running
What do I need to run Datronome?
On Windows 10 or 11 (64-bit), download the installer and run it: everything Datronome needs is included, and it does not need administrator rights. On Mac or Linux, or if your IT team prefers it, the zip runs with Python 3.11 or newer. No Docker, no database server, no cloud account.
Does Datronome run on Windows?
Yes, natively; Windows is the primary platform. Command tasks run in Command Prompt, SQL Server connects through ODBC with Windows authentication, and Task Scheduler can start Datronome at login.
Can a team use Datronome?
Yes. Owners manage people, editors build and run pipelines and decide approvals, viewers can look and download. New people get a temporary password and choose their own on first sign-in. Single sign-on is on the Enterprise roadmap.
Can I deploy Datronome on a server?
Yes, with Docker or as a plain Python process behind HTTPS. A hardened mode disables Python and command tasks so a server only runs SQL, API and check steps.
Is there version control?
Every save is a version you can restore. Pipelines can be pushed to and pulled from a GitHub repository as JSON files, and a sample GitHub Actions workflow shows how to check them on every pull request and deploy them to a Datronome server on merge.
Security
How does Datronome protect passwords and secrets?
Passwords are hashed with scrypt. Secrets such as database passwords and API keys are encrypted on disk under a key only your user account can read, substituted into tasks only at run time, and masked out of every log line.
Is Datronome secure enough for company data?
It ships with the standard defenses: hashed passwords, encrypted secrets, session and CSRF protection, login lockout, strict browser security headers, role-based access, and an audit log. It has not yet had a third-party penetration test or SOC 2 audit; those are planned before enterprise contracts.
Who can run code through Datronome?
Anyone with the Editor or Owner role can add Python and command tasks that run as the Datronome service account. Treat editor access like access to the machine, or run the server in hardened mode where those task types are disabled.
Support and refunds
How do I get support?
By email, at the address on the contact page (paid customers also find it in their licence key email), answered within one business day. We do not offer phone support and we do not schedule support calls: one written thread keeps the exact error text and the history, which is how a small vendor answers everyone the same day.
What is your refund policy?
You can request a full refund within 7 days of first use of a paid plan. After 7 days of use we do not issue refunds, but you can cancel at any time and the licence stays active until the end of the period you already paid for. If you were charged but never installed, we refund it as a courtesy whenever you ask.
How do I cancel?
From Settings → Plan → Manage billing inside Datronome, or by email. Cancelling stops the next renewal; your key stays valid to the end of the paid period plus 7 days.
Why is there a free Starter plan?
So you can evaluate Datronome for as long as you like before paying, instead of relying on a short trial and a refund. Starter includes five pipelines, quality checks, approvals with the decision log, and the AI assistant, with no time limit.
Pricing
How much does Datronome cost?
Starter is free: five pipelines, quality checks, approvals and the decision log, 500 MB of files, the AI assistant (local, or cloud with your own key), one computer. Team and Enterprise are monthly subscriptions with one flat price per company, not a price per person; each plan has a limit on pipelines and people. Current prices are on the pricing page. Cancel any time.
Is there a free trial?
The Starter plan is free without a time limit. Paid plans can be cancelled any time; the key stays valid to the end of the paid period plus 7 days.
Do I buy Datronome or subscribe to it?
You subscribe. A paid plan is a monthly licence to use Datronome while the subscription is active; you don't buy or own the software. If the subscription ends (after the paid period plus 7 days), the paid features stop and Datronome goes back to the free Starter plan: pipelines beyond five are paused, never deleted, and on a team server only the owner can sign in. Renewing turns everything back on.
Can I pay by invoice or purchase order?
Yes, for Enterprise. Ask for a quote and we issue the license key by hand when the invoice is paid.
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