Actual Budget
Every unit of income gets a job in Actual Budget - a local-first personal finance app built on envelope (zero-sum) budgeting, where you can only budget cash you actually have, which keeps the plan honest by construction. The data model is a SQLite file that lives on your device and works fully offline; the self-hosted Node.js sync server adds background multi-device synchronization using CRDT-based distributed-systems machinery, browser and mobile access as an installable web app, and automated backups. Optional end-to-end encryption makes the synced data unreadable even to the server hosting it. Transactions enter three ways: manual entry, file import (CSV, QIF, OFX, QFX, CAMT.053), or automatic bank syncing through GoCardless for EU/UK banks and SimpleFIN for US/Canada. Built-in YNAB4 and nYNAB importers migrate complete budget histories, and reports, schedules for recurring transactions, and rule-based transaction cleanup handle the day-to-day. A fully featured local API lets developers script custom importers and automation against their own data. 100% free, open source, and 26k stars strong.
Monetr
After the bills are covered, how much is actually safe to spend? monetr organizes an entire budgeting application around that one question. Inspired by the defunct Simple bank, it budgets paycheck by paycheck rather than month by month. Funding schedules encode when you get paid - including multiple schedules per account and a weekend-exclusion option for deposits that land early - and every expense or savings goal is tied to one. monetr then calculates how much of each recurring obligation (rent, car payment, subscriptions, on any repeat interval) to set aside from each paycheck, so a large bill never has to come out of a single check. What remains after allocations is surfaced as Free-To-Use, and a forecasting timeline projects contributions, due dates, and leftover funds forward so low-balance periods are visible before they happen. Transactions arrive either as OFX uploads from your bank or automatically through a Plaid connection using your own API credentials, keeping balances and transactions synced without manual entry. The app is mobile-friendly and installable as a PWA on desktop or phone. Self-hosting via Docker Compose is completely free, with all source code public and your financial data on your own hardware.
Hammond
When Clarkson, the once-popular fuel logger, stopped receiving updates, Hammond stepped in as its logical successor - a self-hosted vehicle expense tracker. Written in Go with a Vue.js interface and SQLite storage - a single lightweight container, no external database - it tracks every cost your vehicles generate: fuel fill-ups with cost, volume, and odometer readings; maintenance and repairs; and arbitrary other expenses, each attachable with photos and documents stored against the vehicle. The multi-user, multi-vehicle design is what sets it apart from phone apps: a household or small business adds all its vehicles and all its drivers, shares vehicles across users, and every fill-up lands in one ledger no matter who was driving. The Quick Entries feature respects how expenses actually happen - snap a photo of the receipt or pump screen at the gas station, then complete the structured entry later when you have a minute. Reporting works at both the vehicle level (cost per distance, fuel economy trends) and across the whole fleet. Migration matters here: importers for Clarkson, Fuelly, and Drivvo bring years of fill-up history along, so switching does not mean starting your data over.
ExpenseOwl
Log a date, amount, and category; get a clean monthly pie chart and a cashflow strip showing income, expenses, and net balance - ExpenseOwl is expense tracking stripped to what actually matters. The MIT-licensed Go application deliberately is not a budgeting system - no envelopes, no accounts, no double-entry, no bank sync - because its author found tools like Firefly III and Actual too heavy for the simple question "where did this month's money go?" The dashboard makes that question fast: click a pie slice to exclude fixed costs like rent and see discretionary spending clearly, then drill into a chronological table view to inspect or delete individual transactions. Recurring transactions handle salaries and subscriptions automatically, optional tags add a second classification axis, and settings cover custom categories, currency symbol, and a configurable month start date for non-calendar pay cycles. CSV import migrates data from virtually any other tool, and CSV export keeps your data portable. It ships as a self-contained binary and multi-architecture Docker image with zero internet interaction, stores data in flat JSON files by default (PostgreSQL optional), and installs as a PWA on phones. Single-user by design; pair it with an authenticating reverse proxy if exposed publicly.
Wally
Started as an ExpenseOwl-inspired project, Wally grew into a lightweight, self-hosted expense tracker more capable in every direction its author touched. The backend is Python FastAPI over SQLite, which means every deployment ships a full REST API with interactive documentation at /api/docs - automating imports or wiring in external tools requires no reverse engineering, and when the optional login page is enabled you can mint scoped API keys from the Settings page for token-based integrations. The transactions view is built on AG Grid, bringing real search, column sorting, and per-column filtering to your ledger, with a footer totaling rows, income, and expenses for whatever slice you have filtered. Dashboards go beyond the usual monthly doughnut: a Change button swaps in year-scale line graphs so you can track a single category - restaurants, say - across time. Recurring transactions edit intelligently, letting you apply changes to all instances or only future ones. CSV import and export use a simple six-column format handled from Settings, the refined dark theme is genuinely easy on the eyes, and the interface is translated into more than ten languages. The whole thing runs from one small container with a single data volume.