Learn how Flexprice and Lago differ in their key features, development activity, technology stack and community adoption, so you can decide which of these subscription & billing management tools is best for you.
Last 30 days
Last commit
9 hours agoRepository age
2 yearsVersion
v2.1.48License
AGPL-3.0Repository
flexprice/flexprice
Last 30 days
Last commit
2 days agoRepository age
5 yearsVersion
v1.57.0License
AGPL-3.0Self-hosted
YesRepository
getlago/lago
Lago appears to have several advantages over Flexprice, particularly in popularity, growth, maturity and features. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Lago leads in popularity with 10,776 stars vs 6,873 stars for Flexprice. The 57% higher star count indicates stronger community adoption. In terms of developer contributions, Flexprice has 956 forks, indicating moderate developer engagement.
Lago is growing faster, adding 112 stars in the last 30 days (+1.1%) against losing 5 stars for Flexprice (-0.1%). Lago is both larger and pulling further ahead.
Both projects show recent activity, with Flexprice last updated 9 hours ago and Lago 2 days ago.
Both tools share common technology foundations, being built with Bash, Golang. However, they differ in their additional technology choices: Flexprice uses JavaScript, Python.
Lago has been in development longer, starting 5 years ago, compared to Flexprice which began 2 years ago. This 2.7-year head start suggests Lago may have more mature features and established processes.
Both projects use the AGPL-3.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in Subscription & Billing Management. However, they also have distinct specializations: Flexprice also focuses on Cloud Cost & Optimization while Lago extends into Payment Infrastructure.
Lago provides self-hosting options for complete data control and customization, while Flexprice may be primarily cloud-based or require different deployment approaches.