---
title: "Firebase vs AWS Amplify vs Supabase: BaaS Comparison 2026"
author: "Nate Laquis"
author_role: "Founder & CEO"
date: "2028-08-01"
category: "Technology"
tags:
  - Firebase vs AWS Amplify vs Supabase
  - BaaS comparison
  - backend as a service
  - serverless backend
  - cloud platform comparison
excerpt: "Three BaaS platforms, three very different philosophies. This guide cuts through the marketing and compares Firebase, AWS Amplify, and Supabase on what actually matters: data model, auth, pricing curves, and how painful it is to leave."
reading_time: "14 min read"
canonical_url: "https://kanopylabs.com/blog/firebase-vs-aws-amplify-vs-supabase"
---

# Firebase vs AWS Amplify vs Supabase: BaaS Comparison 2026

## Why the BaaS Decision Is a One-Way Door

Backend as a Service platforms promise the same thing: skip the infrastructure work, ship your app, and worry about scaling later. In 2026, three platforms dominate the BaaS landscape. **Firebase** remains Google's flagship, backed by a decade of production usage across millions of apps. **AWS Amplify** connects you to the full depth of Amazon Web Services through an opinionated frontend-developer-friendly layer. **Supabase** is the open-source challenger built on PostgreSQL, growing fast and attracting teams that value data ownership and SQL flexibility.

Choosing between them is not like picking a UI library you can swap out in a weekend. Your BaaS dictates your data model, your query language, your authentication architecture, your real-time strategy, and your billing structure. Once you have 50 database tables, a few thousand users, and business logic wired into vendor-specific triggers, migrating off a platform takes months of engineering time and introduces real risk of data loss or downtime.

At Kanopy, we have built and shipped production applications on all three platforms. We have migrated teams off Firebase when its NoSQL model became a bottleneck, helped startups untangle themselves from Amplify's code generation when it stopped matching their architecture, and deployed Supabase backends that scaled to hundreds of thousands of active users. This comparison comes from that hands-on experience, not spec-sheet reading.

![Developer writing backend code on a laptop with multiple terminal windows open](https://images.unsplash.com/photo-1555949963-ff9fe0c870eb?w=800&q=80)

We will cover database architecture, authentication, real-time capabilities, serverless functions, pricing, scalability, and vendor lock-in across all three platforms. By the end, you will know exactly which BaaS fits your product, your team size, and your long-term trajectory.

## Database Architecture: Three Fundamentally Different Models

The database layer is where these three platforms diverge most dramatically, and it is the single most important factor in your decision. Your database choice shapes every query you write, every data migration you run, and every feature you build on top of it.

### Firebase: Firestore (Document-Collection NoSQL)

Firestore organizes data into collections of documents. Each document is a JSON-like object that can contain nested fields, arrays, and subcollections. There is no enforced schema, which means two documents in the same collection can have completely different fields. This flexibility is great for prototyping but becomes a liability as your data model matures.

The biggest limitation is the absence of joins. If you need to display a user's orders along with product details, you make separate queries to the users, orders, and products collections and stitch the results together in your application code. Teams compensate by denormalizing data (duplicating product names and prices into order documents), which creates consistency challenges when that duplicated data changes. Firestore also restricts complex queries: you cannot do inequality filters on multiple fields without composite indexes, and there is no full-text search built in.

### AWS Amplify: DynamoDB, Aurora, or AppSync GraphQL

Amplify's data layer is more flexible than most people realize, but that flexibility comes with complexity. The default path uses **AWS AppSync** (a managed GraphQL service) backed by **DynamoDB** tables. You define a GraphQL schema, Amplify generates resolvers and DynamoDB tables, and your frontend queries data through GraphQL. DynamoDB is a key-value/document store optimized for single-digit-millisecond reads at any scale, but it requires careful access pattern planning upfront. If you need a query pattern you did not design for, you may need to add a Global Secondary Index or restructure your table.

Amplify Gen 2 (the TypeScript-first rewrite) also supports connecting to **Aurora Serverless** (PostgreSQL or MySQL) or existing RDS instances. This gives you full relational database capabilities, but the integration is less polished than the DynamoDB path. You lose some of Amplify's automatic code generation and need to manage more of the data access layer yourself.

### Supabase: Full PostgreSQL

Supabase gives you a dedicated PostgreSQL instance with every extension, data type, and query capability the engine supports. Foreign keys, constraints, joins, window functions, CTEs, recursive queries, full-text search with `tsvector`, geospatial queries with PostGIS, and vector similarity search with pgvector for AI features. If PostgreSQL can do it, your Supabase database can do it.

Row-Level Security policies run at the database level, eliminating an entire class of authorization bugs. Schema changes are explicit SQL migrations managed through the Supabase CLI, Prisma, or Drizzle Kit. And because it is standard PostgreSQL, you can connect any client, ORM, or analytics tool directly. Your data is never trapped behind a proprietary API.

**Bottom line:** If your data is relational (users, organizations, projects, invoices, subscriptions), Supabase wins on query power and developer experience. If you need extreme read throughput with predictable access patterns, DynamoDB through Amplify is purpose-built for that. Firebase's Firestore works for simple, shallow data models but forces painful workarounds the moment relationships get complex. For a deeper dive into [Supabase vs Firebase specifically](/blog/supabase-vs-firebase), see our dedicated comparison.

## Authentication and Authorization Compared

Authentication is table stakes for any BaaS. All three platforms handle sign-up, sign-in, password reset, and OAuth providers. The differences are in how auth connects to your data layer and how much control you have over the user lifecycle.

### Firebase Authentication

Firebase Auth is battle-tested across millions of apps. It supports email/password, phone OTP, anonymous auth (great for guest-to-registered conversion flows), and OAuth with Google, Apple, GitHub, Microsoft, and more. Multi-factor authentication is built in via SMS and TOTP. Firebase Auth tokens integrate with Firestore Security Rules, which let you write access control policies in a custom DSL. The rules are powerful but have a steep learning curve, and debugging them in production is notoriously painful because errors are opaque and the rules simulator has known gaps.

### AWS Amplify Auth (Amazon Cognito)

Amplify wraps **Amazon Cognito** for authentication. Cognito supports email/password, phone, social providers, SAML federation for enterprise SSO, and custom auth flows with Lambda triggers. It is the most enterprise-ready option of the three: if your customers need SAML or OIDC federation with their corporate identity provider, Cognito handles it natively. The downside is complexity. Cognito's configuration surface is enormous, error messages are cryptic, and the developer experience lags behind Firebase and Supabase. Amplify's abstraction layer helps, but you still hit raw Cognito edges when you need to customize token claims, adjust password policies, or handle migration from another auth provider.

### Supabase Auth

Supabase Auth is built on GoTrue, an open-source auth server. It supports email/password, magic links, phone OTP, and 30+ OAuth providers. The killer feature is the integration with PostgreSQL Row-Level Security. Your database policies reference `auth.uid()` directly, which means authorization logic lives in the database, not in application middleware or a separate rules engine. This is cleaner, easier to test, and harder to get wrong. Supabase added MFA support (TOTP) in 2024 and has steadily expanded enterprise features like SSO with SAML.

**Bottom line:** For enterprise SSO and SAML federation, Cognito through Amplify is the most mature option. For developer experience and auth-to-database integration, Supabase leads. Firebase sits in the middle with the broadest built-in MFA options and the longest track record at scale.

## Real-Time, Edge Functions, and the Serverless Stack

A modern BaaS is more than a database and an auth layer. Real-time data sync and serverless compute round out the stack. Here is how each platform approaches them.

### Real-Time Capabilities

**Firebase** was built for real-time from day one. The original Realtime Database synchronizes a JSON tree across all connected clients instantly. Firestore added `onSnapshot` listeners that push document changes to clients within milliseconds. Firebase's real-time infrastructure is arguably the most battle-hardened in the industry, trusted by apps serving millions of concurrent connections.

**Supabase Realtime** uses PostgreSQL's logical replication to broadcast INSERT, UPDATE, and DELETE events over WebSockets. It also supports Broadcast (pub/sub messaging) and Presence (tracking online users in a channel). The implementation is production-ready but younger and less tested at Firebase-scale concurrency.

**AWS Amplify** handles real-time through **AppSync subscriptions**, which are GraphQL subscriptions over WebSockets. You define subscription types in your schema, and AppSync pushes data to connected clients when mutations occur. The approach is clean and type-safe if you are already using AppSync's GraphQL layer. Outside of GraphQL, Amplify can connect to **AWS IoT Core** for MQTT-based real-time messaging, but that requires significantly more configuration.

![Real-time analytics dashboard showing live data feeds and monitoring charts](https://images.unsplash.com/photo-1551288049-bebda4e38f71?w=800&q=80)

### Serverless Functions

**Supabase Edge Functions** run on Deno Deploy at the edge. They support TypeScript natively, have minimal cold starts (typically under 50ms), and can query your PostgreSQL database directly. Deploy with a single CLI command.

**Firebase Cloud Functions** run on Google Cloud Functions (Node.js, Python, or Go). They integrate tightly with Firebase triggers: a Firestore write can automatically invoke a function. Cloud Functions v2 (built on Cloud Run) improved cold start performance and added concurrency support, but cold starts of 1-3 seconds are still common for Node.js functions that have not been invoked recently.

**AWS Amplify Functions** are **AWS Lambda** functions under the hood. Lambda supports Node.js, Python, Go, Java, .NET, and custom runtimes. You get the full power of the AWS ecosystem: connect to SQS queues, process S3 uploads, invoke Step Functions workflows. The trade-off is configuration overhead. A Lambda function that triggers on a DynamoDB stream requires IAM roles, event source mappings, and retry policies that Amplify partially abstracts but does not fully hide.

**Bottom line:** Firebase leads on real-time maturity. Supabase leads on edge function simplicity and cold start performance. Amplify gives you the broadest serverless ecosystem but demands more configuration knowledge. If real-time sync is your primary use case, Firebase is still the safest bet. For everything else, Supabase and Amplify are both strong, with different complexity profiles.

## Pricing: Free Tiers, Growth Curves, and Surprise Bills

Every BaaS offers a generous free tier. What matters is the cost curve as you scale, and whether the pricing model aligns with how your application actually uses resources. We have seen teams hit unexpected bills on all three platforms, but some pricing models are more predictable than others.

### Firebase Pricing

Firebase's free Spark plan is genuinely generous for prototyping: 1 GiB Firestore storage, 50K daily reads, 20K daily writes, and 20K daily deletes. The Blaze plan (pay-as-you-go) charges per operation. In 2026, Firestore charges roughly $0.06 per 100K reads, $0.18 per 100K writes, and $0.02 per 100K deletes, plus $0.18/GiB/month for storage. Cloud Functions are billed per invocation, GB-second, and networking.

The danger with Firebase pricing is that it scales with operations, not users or compute time. A single page load that triggers 50 Firestore reads across multiple collections adds up fast. Teams building data-heavy dashboards or admin panels regularly report monthly bills jumping from $50 to $500 overnight when a feature increases read counts. There is no spending cap on the Blaze plan, so runaway queries can generate four-figure bills before anyone notices.

### AWS Amplify Pricing

Amplify pricing is a patchwork of the underlying AWS services. DynamoDB charges per read/write capacity unit (on-demand mode: $1.25 per million write request units, $0.25 per million read request units). AppSync charges $4 per million query and data modification operations plus $2 per million real-time updates. Cognito is free for the first 50,000 monthly active users, then $0.0055 per MAU. Lambda charges $0.20 per million invocations plus $0.0000166667 per GB-second.

The complexity is the problem. An Amplify app might touch six different AWS billing meters (DynamoDB, AppSync, Cognito, Lambda, S3, CloudFront), each with its own pricing unit. Predicting your monthly bill requires a spreadsheet. AWS does offer cost alerts and budgets, but the granularity of billing makes it hard for early-stage teams to forecast costs until they have a few months of production data.

### Supabase Pricing

Supabase pricing is simpler. The free tier includes 500 MB database storage, 1 GB file storage, 50,000 monthly active users for auth, and 500,000 Edge Function invocations. The Pro plan is $25/month and includes 8 GB database storage, 100 GB file storage, and 100,000 MAU. Beyond that, usage-based pricing applies: $0.125/GB for additional database storage, $2 per 100,000 MAU beyond the included amount.

The key advantage is predictability. Because Supabase charges primarily by storage and MAU rather than per-operation, a complex query that joins five tables costs the same as a simple primary key lookup. You are not penalized for building features that read data frequently, which removes a perverse incentive that exists on Firebase.

**Bottom line:** Supabase has the most predictable pricing model. Firebase is cheap to start but can surprise you at scale. Amplify inherits AWS's powerful-but-complex billing. For a seed-stage startup burning through its first $100K, Supabase's flat Pro plan at $25/month is hard to beat. For enterprise teams already on AWS with existing billing agreements, Amplify's per-service pricing may actually be cheaper at high volume.

## Vendor Lock-In, Portability, and Long-Term Risk

Lock-in is the elephant in every BaaS conversation. Platforms want you to stay. Your job is to understand exactly how deep the hooks go before you commit.

### Firebase: High Lock-In

Firebase is the most locked-in option of the three. Firestore uses a proprietary data model and query language accessible only through Firebase SDKs. Security Rules are a custom DSL that exists nowhere else. Cloud Functions are tightly coupled to Firebase triggers. If you decide to leave Firebase, you need to export your Firestore data (possible, but the output is JSON documents that need to be reshaped for any relational database), rewrite your auth system, rewrite your real-time subscriptions, and rewrite your serverless functions. We have done this migration for clients. It typically takes 2-4 months for a mid-complexity app.

### AWS Amplify: Medium Lock-In

Amplify sits on top of standard AWS services. DynamoDB is proprietary, but it has well-documented export paths. Cognito user pools can be migrated (painfully) to other identity providers. Lambda functions are portable if you did not lean too hard on AWS-specific event shapes. The GraphQL schema is standard, but AppSync's resolver mapping templates (VTL-based) are AWS-specific. The saving grace is that you can gradually peel back the Amplify abstraction and interact with the underlying AWS services directly, giving you an escape hatch that Firebase does not offer. If your team already runs infrastructure on AWS, Amplify's lock-in is less concerning because you are locked into an ecosystem you already chose.

### Supabase: Low Lock-In

Supabase has the strongest portability story. Your database is standard PostgreSQL. Your auth tokens are standard JWTs. Your Edge Functions are standard Deno/TypeScript. If you outgrow Supabase or want to self-host, you can take your PostgreSQL dump and run it on any PostgreSQL provider: AWS RDS, Google Cloud SQL, Neon, CockroachDB, or your own server. Row-Level Security policies are standard PostgreSQL features that work identically on any PostgreSQL host. Supabase is also fully open source, so you can self-host the entire platform if you want complete control.

For more context on how Supabase compares to newer challengers in the open-source BaaS space, see our [Convex vs Supabase vs Appwrite comparison](/blog/convex-vs-supabase-vs-appwrite).

![Server room with rows of cloud infrastructure hardware and blinking network lights](https://images.unsplash.com/photo-1504868584819-f8e8b4b6d7e3?w=800&q=80)

**Bottom line:** If portability and data ownership are priorities, Supabase is the clear winner. Amplify offers a middle ground with standard AWS services underneath. Firebase demands the most commitment and the most work to leave. For a detailed comparison of the cloud providers behind these platforms, check our [AWS vs Google Cloud vs Azure breakdown](/blog/aws-vs-google-cloud-vs-azure).

## Which BaaS Should You Choose in 2026?

After building on all three platforms and migrating teams between them, here is our honest recommendation framework. There is no universally best BaaS. There is a best BaaS for your specific situation.

### Choose Firebase If:

- **Real-time sync is your core feature.** Collaborative apps, chat, multiplayer games, live dashboards. Firebase's real-time infrastructure is unmatched in maturity and latency.

- **You are building a mobile-first app** and want tight integration with analytics, crash reporting (Crashlytics), push notifications (FCM), and remote config. Firebase's mobile SDK ecosystem is the deepest available.

- **Your data model is simple and document-shaped.** User profiles, settings, chat messages, and feed items fit Firestore's model well. If you do not need joins or complex queries, Firestore's limitations will not bother you.

- **Your team already knows Firebase.** Developer familiarity cuts onboarding time in half. If your engineers have built three apps on Firebase, switching to Supabase or Amplify has a real productivity cost.

### Choose AWS Amplify If:

- **Your company is already on AWS.** If you have existing VPCs, IAM policies, S3 buckets, and billing agreements, Amplify plugs into that ecosystem without introducing a new vendor relationship.

- **You need enterprise-grade identity management.** SAML federation, Cognito user pools with custom attributes, and Lambda-triggered auth flows give you flexibility that Firebase and Supabase cannot match today.

- **You anticipate needing AWS services beyond BaaS.** Machine learning with SageMaker, media processing with MediaConvert, IoT with AWS IoT Core. Amplify is your on-ramp to the full AWS catalog.

- **You have experienced AWS engineers on the team.** Amplify smooths over many AWS rough edges, but when something breaks, you will debug it using AWS-native tools and concepts. A team without AWS experience will struggle.

### Choose Supabase If:

- **Your data is relational.** Users, organizations, projects, tasks, invoices, subscriptions. If your app has foreign keys and needs joins, PostgreSQL will save you hundreds of hours compared to Firestore or DynamoDB.

- **You want predictable pricing.** Supabase's $25/month Pro plan covers most early-stage apps without per-operation billing surprises.

- **Portability matters to your team or your investors.** Open-source foundations and standard PostgreSQL mean you are never trapped. This is increasingly important for startups raising funding, because savvy investors ask about infrastructure lock-in during due diligence.

- **You value developer experience.** Supabase's dashboard, CLI, local development environment, and documentation are consistently rated the best in the BaaS space. Getting from zero to a deployed backend takes under 10 minutes.

For most startups building B2B SaaS, internal tools, or data-heavy consumer apps in 2026, **Supabase is our default recommendation**. The combination of PostgreSQL, predictable pricing, low lock-in, and excellent developer experience makes it the safest long-term bet for the widest range of applications. Firebase remains the best choice for real-time-heavy mobile apps, and Amplify is the right call when you need to plug into a broader AWS ecosystem.

If you are weighing these platforms for a specific project and want an expert opinion on which one fits your architecture, [book a free strategy call](/get-started) with our team. We will review your requirements, data model, and growth plan, then recommend the BaaS that sets you up for the least friction over the next two years.

---

*Originally published on [Kanopy Labs](https://kanopylabs.com/blog/firebase-vs-aws-amplify-vs-supabase)*