The choice of backend for a mobile application is determined by a number of factors: data structure requirements (NoSQL vs SQL), scalability, cost, development speed, ecosystem and support, real-time and offline capabilities, and the level of control over the infrastructure. Popular off-the-shelf solutions include Firebase, Supabase, AWS Amplify, Backendless, and other MBaaS/BaaS platforms. For projects with special requirements (compliance, complex transactions), classic relational DBMS (MySQL, PostgreSQL) or GraphQL-based build (Hasura) or headless CMS (Strapi) are often used. Below is a detailed breakdown of the key options and selection criteria.
Introduction: why you need a backend and what approaches there are
The backend is responsible for data storage and processing, authorization, business logic, integration with external services and push notifications.
There are three main approaches:
- MBaaS/BaaS – off-the-shelf cloud platforms with SDKs and APIs (Firebase, AWS Amplify).
- Headless CMS – content management solutions suitable for mobile apps (Strapi).
- Custom backend – independent development based on relational or NoSQL DBMS and frameworks (e.g. Node.js + MySQL, Hasura).
Key selection criteria
1. Data structure and query language
NoSQL (document model) supports flexible schemas and rapid prototyping (Firebase Realtime Database, Firestore).
SQL (relational DBMS) provides transactionality, complex relationships and powerful analytics capabilities (PostgreSQL/Supabase, MySQL).
2. Real time and offline mode
Firebase supports real-time synchronization and offline mode out of the box.
Supabase implements real-time through PostgreSQL subscriptions, offline mode requires additional implementation on the client.
3. Cost and pricing model
Firebase is billed by read/write/delete operations, which can lead to unexpectedly high bills when the load grows.
Supabase offers predictable pricing: payment for the amount of stored data and functions, without limits on API requests.
4. Scalability and performance
Firebase is highly scalable thanks to Google Cloud infrastructure.
Supabase benchmarks show up to 4× faster reads and 3.1× faster writes compared to Firebase.
4. Scalability and performance
Firebase is highly scalable thanks to Google Cloud infrastructure.
Supabase benchmarks show up to 4× faster reads and 3.1× faster writes compared to Firebase.
5. ecosystem and support
Firebase extensive Google ecosystem: ML Kit, Analytics, Crashlytics, etc.
Supabase open source, active community, self-hosting capability.
AWS Amplify is integrated into the AWS ecosystem, supports multiple services (Cognito, S3, AppSync).
Backendless offers low-code/visual-designer, real-time and SQL queries in GUI.
Overview of popular MBaaS/BaaS and headless solutions
Firebase
Platform from Google with Firestore, Authentication, Cloud Functions, Cloud Storage, etc.
Pros: instant start, real-time, SDK for all platforms.
Cons: complex NoSQL queries, unpredictable billing.
Supabase
Open alternative to Firebase based on PostgreSQL, with real-time, Auth, Storage, Edge Functions.
Pros: SQL-power, transparent pricing, self-host.
Cons: younger ecosystem, fewer ready-made services.
AWS Amplify
CLI and Studio for building AWS backend resources: GraphQL/REST API (AppSync), Authentication (Cognito), Storage (S3) and features (Lambda).
Pros: powerful AWS ecosystem, CI/CD, TypeScript support.
Cons: steep learning curve, possible AWS overhead.
Backendless
MBaaS with visual tools for schema, functions without code, real-time DB and REST/GraphQL API.
Pros: low-code, fast build, graphical editor.
Cons: less known, limited integrations.
Strapi (Headless CMS)
Open-source CMS, content is delivered via REST/GraphQL API, suitable for PWA and native applications.
Pros: flexible content model, ready-to-use administration panel.
Cons: primarily CMS solution, not focused on real-time.
Traditional DBMSs and custom solutions
MySQL
Popular RDBMS for structured data, high performance and security.
According to Statista, 46.85% of developers will use MySQL in 2022.
When to choose:
- Need full customization and control.
- Need complex transactions and rigorous SQL.
Hasura
GraphQL engine on top of PostgreSQL, generates API with authorization and real-time from the database in one click.
When to choose:
- Love GraphQL and want an instant backend.
- Need minimal pipelining over SQL and real-time ready.
Comparative table
| Solution | DB Type | Real‑time | Pricing | Open‑source | Query language |
|---|---|---|---|---|---|
| Firebase | NoSQL | ✔ | PAYG (read/write/delete) | ❌ | NoSQL/REST |
| Supabase | PostgreSQL | ✔ | Storage fees | ✔ | SQL |
| AWS Amplify | DynamoDB/Postg | ✔ through AppSync | PAYG AWS (resources) | ❌ | GraphQL/REST |
| Backendless | Real‑time SQL | ✔ | Fixed tariff + PAYG functions | ❌ | SQL/REST |
| Strapi | Any (Postg) | ✘ | Fixed rate/self-hosting | ✔ | REST/GraphQL |
| MySQL | Relational | ✘ | Depends on the host | ✔ | SQL |
| Hasura | PostgreSQL | ✔ | Self-hosted/managed Cloud | ✔ | GraphQL |
Recommendations for selection
Prototype or MVP: Firebase or AWS Amplify for fast builds.
Complex business logic and analytics: Supabase or custom MySQL/PostgreSQL.
Content-centric applications: Strapi or similar headless CMS.
GraphQL-fans: Hasura for instant GraphQL backend.
Low-code/Visual: Backendless for accelerated prototyping with minimal code.
Conclusion
When selecting a backend, it is important to consider a combination of factors: data model, realistic scale and cost requirements, ecosystem, team experience, and project specifics. Off-the-shelf BaaS/MBaaS solutions speed development, but can limit flexibility and lead to unpredictable costs. Traditional DBMS and custom solutions give you maximum control, but require more resources for development and support.
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