We Switched From Firebase to Supabase: Here is What Changed

Change is the law of nature. It’s not necessary if a tool worked initially, it won’t turn obsolete. Thus, we switched to another tool, & here’s what we learnt.

We were working on our workflow app at Wokegenics when we hit a wall. Everything was running on Firebase. But as we grew, costs rose quickly, and real-time updates slowed down. That is when we decided to try Supabase. We wanted to see if this change could drive better performance and lower costs. Thus, we switched from. And here is what changed.

Tool Comparison: Firebase vs Supabase

What we used before: Firebase
We loved Firebase for its real-time database, easy SDKs, and automatic scaling. It was our go-to choice for chat features and live updates. However, it came with caveats: query limits, unpredictable billing, and some lag as we crossed 5,000 users.

What we switched to: Supabase
Supabase offered Postgres under the hood, real-time subscriptions via websockets, and predictable billing. It also gave us SQL queries, row-level security, and built-in storage. We felt it might be a better long-term fit.

Before and After Data

1. Cost Per Month

Firebase: Started at $450/month. Swelled to $1,500/month once we hit 8K users, based on our billing dashboard and Firebase’s usage-based pricing.
Supabase: Our billing stayed steady at $500/month even as usage grew. We immediately saved 67% in running costs.

What it means: We went from hitting surprise bills to clear budgeting. It gave us space to focus on our product.

2. Response Time (Realtime Updates)

Firebase: Average update delay was 350ms with 5,000–7,000 active users.
Supabase: Supabase real-time showed ~120ms update time in our k6 tests, compared to Firebase’s 300–600ms average in high-load sessions.

What it means: Users now see changes faster. That small speed boost made collaborative editing feel instant.

3. Developer Experience

Firebase: NoSQL meant more code in cloud functions. Harder to debug and scale logic.
Supabase: Filtering dashboard data by active sessions used to require 20+ lines in Firebase functions. In Supabase, it became a single SQL query. The debugging was instant.

What it means: Our team now moves twice as fast when building backend features.

4. Scalability / Errors

Firebase: As traffic scaled to 8K users, we saw 2–3 timeout errors daily.
Supabase: Since migration, only 1 minor timeout in 60 days, thanks to Postgres indexing and caching.

What it means: Less firefighting. More focus on creating useful features.

What We Learned

Single-vendor convenience costs more
Firebase made early development easy. But when usage grew, so did costs and limits.
SQL + managed databases offer longevity
Supabase’s SQL model allowed better reasoning, easier scaling, and future flexibility.
Reliability fuels trust
Fewer timeouts and faster updates meant happier users and better onboarding numbers.

Dev experience matters as much as runtime
If a tool makes your team more productive, that is a massive win.

Conclusion

Switching from Firebase to Supabase, we noticed a ~60–70% drop in costs based on monthly billing summaries, and sped up real-time updates from 350ms to 120ms. Error logs fell dramatically from a few daily timeouts to one in two months, while doubling our backend productivity, as tasks that earlier took 2 hours now often take 1. That speed boost made our app feel more responsive, and users noticed. These were not just metrics; they translated to a happier team and happier users.

However, these results reflect our specific use case, app size, and traffic levels. Your results may vary based on workload and implementation.

Want to Scale the Right Way?

At Wokegenics, we do not settle. We test tools, benchmark performance, and switch when something better comes along. If you are building a tech product and want help choosing the right stack or migrating with minimal risk, let us chat. We are here to help you build what both you and your users love.