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SPECIFICTION
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dbdiff vs driftcurve

dbdiff

rekurt.github.io

driftcurve

github.com

Side by side

Figuredbdiffdriftcurve
Price from—Free
Free plan—Yes
Free trial——
Open source—Yes
Web—Yes
WindowsYes—
macOSYes—
LinuxYes—
API—Yes
Self-hostedYesYes
Plans published01
Spec score · Database Schema Comparison Tools7.7 (#10)8.5 (#2)
LicenseThe project page identifies the license as MIT.The project is open source under the Apache License 2.0.
PurposeDBDiff compares local or remote databases and generates a migration file for their differences.driftcurve is a household retirement planning engine that models household finances and simulates retirement outcomes.

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dbdiff

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driftcurve

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In their own words

dbdiff

DBDiff is a free, MIT-licensed tool for comparing local or remote MySQL, PostgreSQL, and SQLite databases and generating migrations from schema or data differences. It can produce SQL migrations with up and down changes, using native SQL, Flyway, Liquibase, Laravel, or custom templates. The migration runner can create, apply, roll back, check, validate, repair, and baseline migrations. Listed comparison targets include tables, views, triggers, routines, types, sequences, row-level security policies, and data. Its configuration file can specify connections, drivers, diff scope, included or ignored tables and fields, and row filters. Installation options include pre-built Windows, macOS, and Linux binaries, npm, PHAR, Docker or Podman images, and Composer source. For PostgreSQL, DBDiff also compares row-level security policies and table security flags. By default, generation stops when a migration would drop a table or column, though an option permits those changes. One documented PostgreSQL limitation is that removing or reordering enum labels may leave dependent objects that prevent an automatically generated migration from applying.

Visit rekurt.github.io

driftcurve

driftcurve is an open-source household retirement planning engine for projecting finances and comparing retirement outcomes. It can model multiple household members, account types, debts, mortgages, pensions, Social Security and property sales. Its default Monte Carlo simulations resample annual market data from 1966–2024 across equities, Treasuries, residential real estate, inflation and Bitcoin. Users can adjust historical returns toward their own long-run targets or enter static annual assumptions. Risk-based spending guardrails solve for monthly spending and suggest adjustments based on portfolio thresholds and probability of success. A Compare page puts two scenarios on one chart. In default local mode, household data and saved scenarios stay in browser localStorage, while forecasts run through a Python backend; there is no account or server-side database persistence. Optional multi-user mode adds email/password accounts, server-side sessions, and stored profiles and scenarios. The project offers forecast and guardrails API endpoints, plus authentication, profile and scenario endpoints in multi-user mode. It is free under Apache License 2.0. The maker describes it as an educational modeling tool, not licensed financial, investment, tax or legal advice.

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