Honest, experience-based backend as a service comparison from engineers who have shipped production systems with both.
Firebase vs AWS Amplify: Firebase is the most developer-friendly BaaS with real-time sync and rapid prototyping capabilities. AWS Amplify provides deeper AWS integration and more scalable infrastructure. Firebase ships faster; Amplify scales further. Need help choosing? Get a free consultation →
3
Firebase Wins
0
Ties
3
AWS Amplify Wins
| Criteria | Firebase | AWS Amplify | Winner |
|---|---|---|---|
| Developer Experience | 10/10 | 7/10 | Firebase |
WhyFirebase's console, documentation, and SDKs are best-in-class. Amplify has improved but still has a steeper learning curve and more configuration. | |||
| Real-Time Sync | 10/10 | 6/10 | Firebase |
WhyFirestore and Realtime Database provide seamless real-time synchronization. Amplify can do real-time with AppSync but requires more setup. | |||
| Scalability | 7/10 | 10/10 | AWS Amplify |
WhyAmplify leverages AWS's unlimited infrastructure. Firebase scales well but has limits, and costs can spike unpredictably at high usage. | |||
| AWS Integration | 3/10 | 10/10 | AWS Amplify |
WhyAmplify is built on AWS — full access to Lambda, DynamoDB, S3, Cognito, and 200+ services. Firebase is Google Cloud only. | |||
| Pricing Predictability | 6/10 | 7/10 | AWS Amplify |
WhyFirebase pricing can be unpredictable with Firestore read/write charges. Amplify's AWS pricing is complex but offers more cost control mechanisms. | |||
| Offline Support | 10/10 | 6/10 | Firebase |
WhyFirebase has excellent offline persistence and conflict resolution built-in. Amplify's DataStore provides offline sync but it's less mature. | |||
Scores use a 1–10 scale anchored to production behavior, not vendor marketing. 10 = production-proven at scale across multiple ZTABS deliveries with no recurring failure modes; 8–9 = reliable with documented edge cases; 6–7 = workable but with caveats that affect specific workloads; 4–5 = prototype-grade or stable only in a narrow slice; below 4 = avoid for new work. Inputs: vendor docs, GitHub issue patterns over the last 12 months, our own deployments, and benchmark data cited in the table when applicable.
Vendor-documented numbers and published benchmarks. Sources cited inline.
| Metric | Firebase | AWS Amplify | Source |
|---|---|---|---|
| Cloud provider | Google Cloud (GCP) | AWS | Official docs |
| Primary database option | Firestore (NoSQL) + Realtime Database + Cloud SQL | DynamoDB (NoSQL) + Aurora (SQL) via DataStore / AppSync | firebase.google.com/docs · docs.amplify.aws |
| Auth service | Firebase Authentication (email, phone, OAuth, SAML, anonymous) | Amazon Cognito (user pools, identity pools, SAML, OIDC) | Official docs |
| Firestore read pricing | $0.06 per 100K document reads (after free tier) | DynamoDB: $0.25 per million RCU (on-demand, eventually consistent) | firebase.google.com/pricing · aws.amazon.com/dynamodb/pricing |
| Serverless function runtime | Cloud Functions for Firebase (Node, Python) on Cloud Run v2 | AWS Lambda (many runtimes) behind AppSync/API Gateway | Official docs |
| Offline persistence (client SDK) | Built-in for Firestore and Realtime DB (mobile + web) | Amplify DataStore offline conflict resolution | Official docs |
| Hosting | Firebase Hosting (global CDN + SSL, free tier) | Amplify Hosting (CloudFront + S3, atomic deploys) | Official docs |
| Compliance certifications | SOC 1/2/3, ISO 27001/17/18, HIPAA BAA, PCI DSS | Full AWS compliance stack including FedRAMP, PCI-DSS, HIPAA, SOC 1/2/3, ISO 27001 | firebase.google.com/support/privacy · aws.amazon.com/compliance |
Firebase gets you from zero to working prototype faster than any other BaaS platform.
Amplify's AWS integration provides the compliance, security, and scalability enterprises require.
Firebase's offline persistence and real-time sync are mature and battle-tested for mobile.
If your infrastructure is already on AWS, Amplify provides seamless integration with existing services.
The best technology choice depends on your specific context: team skills, project timeline, scaling requirements, and budget. We have built production systems with both Firebase and AWS Amplify — talk to us before committing to a stack.
We do not believe in one-size-fits-all technology recommendations. Every project we take on starts with understanding the client's constraints and goals, then recommending the technology that minimizes risk and maximizes delivery speed.
Based on 500+ migration projects ZTABS has delivered. Ranges include engineering time, QA, and a typical 15% contingency.
| Project Size | Typical Cost & Timeline |
|---|---|
| Small (MVP / single service) | $8K–$25K, 3–8 weeks. Small app: Firestore → DynamoDB schema redesign (single-table design differs fundamentally from Firestore collections), Firebase Auth → Cognito user-pool migration. Biggest cost is Cognito's UI re-implementation ($2K–$5K) since hosted UI is less polished than Firebase Auth UI. |
| Medium (multi-feature product) | $40K–$160K, 12–26 weeks. Production mobile/web app: Firestore security rules → AppSync resolvers + IAM rewrite dominates ~35% of spend (paradigm shift: client-side rules vs server-side resolvers). Cloud Functions → Lambda + API Gateway/AppSync rewrite is the second largest cost. |
| Large (enterprise / multi-tenant) | $200K–$600K+, 7–14 months. Enterprise app with Firestore + RTDB + FCM + Analytics: full AWS re-platform (Cognito + AppSync + DynamoDB + EventBridge + Pinpoint + Kinesis) — mapping is roughly 1-to-3 in services, each with its own IAM + config. Plan a 120-day dual-write with conflict-resolution strategy; FCM tokens cannot be migrated (devices must re-register via SNS/Pinpoint). |
For mobile-first startups, Firebase's SDKs shave 2-4 weeks off the MVP. For teams already AWS-native, Amplify consolidates cost and ops. Under ~50K MAU both fit; past that, per-read/write fees can dominate — model before committing.
Specific production failures we have seen during cross-stack migrations.
Schemaless storage invites shape changes. Migrations must be app-coded; missed clients read stale shapes for months.
Gen 2 is a major rewrite. Legacy Gen 1 apps and docs confuse teams — verify which you are targeting before building.
Third-way tools and approaches teams evaluate when neither side of the main comparison fits.
| Alternative | Best For | Pricing | Biggest Gotcha |
|---|---|---|---|
| Supabase | Teams wanting Postgres + Auth + Storage + Edge Functions with open-source roots. | Free tier; Pro $25/mo per project. | Real-time is WAL-based and less rich than Firestore listeners for some patterns. |
| Appwrite | Open-source self-hosters who want a broader feature set than Supabase. | Free OSS self-host; Cloud Pro $15/mo. | Smaller community; weaker enterprise-readiness story. |
| Nhost | GraphQL-first BaaS with Hasura + Postgres + Auth managed. | Free tier; Pro from $25/mo per project. | Tiny hiring pool; narrower ecosystem than Firebase. |
| Parse Platform (self-host) | Teams that still run on Parse Server and want open-source continuity. | Free OSS; you pay hosting. | Community maintenance slowing; most greenfield work has moved elsewhere. |
Sometimes the honest answer is that this is the wrong comparison.
Both lock you into a vendor ecosystem. If portability matters, build on Postgres + your own API layer.
Firestore and DynamoDB are both NoSQL-first. Join-heavy data fits Postgres (Supabase) better.
Our senior architects have shipped 500+ projects with both technologies. Get a free consultation — we will recommend the best fit for your specific project.