Pick the wrong backend platform in 2024 and you’d eat the migration cost quietly. Pick wrong in 2026 and your Cognito bill tells the whole company. Supabase, Firebase, and AWS Amplify Gen 2 now cover three very different bets on how a backend should work: flat-rate Postgres with SQL-native security, metered NoSQL with the deepest mobile SDK on the market, or pay-as-you-go AWS primitives wired together with infrastructure-as-code. The gap between them isn’t cosmetic. At 100,000 monthly active users, the identity bill alone can swing by more than $1,000 a month depending on which one you picked, and that’s before a single database read gets counted.
This comparison breaks down current 2026 pricing, database architecture, authentication models, realtime sync, vector search for AI workloads, and what each platform actually costs once an app leaves the free tier behind. All figures below reflect list pricing published on each vendor’s official pricing page as of August 20, 2026.
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Supabase vs Firebase vs AWS Amplify at a Glance
Before diving into each dimension separately, here’s the full specs comparison across the three platforms as they stand in August 2026.
| Feature | Supabase | Firebase | AWS Amplify Gen 2 |
|---|---|---|---|
| Database engine | PostgreSQL (managed) | Cloud Firestore + Realtime Database (NoSQL) | DynamoDB (NoSQL, via AppSync) |
| Free tier database | 500 MB Postgres, 2 projects | 1 GiB Firestore, 50K reads/20K writes daily | 25 GB DynamoDB (AWS Free Tier, 12 months) |
| Entry paid tier | Pro, $25/month flat | Blaze, pay-as-you-go (no flat fee) | No flat tier — pure pay-as-you-go |
| Auth model | Postgres Row-Level Security (RLS), SQL policies | Firebase Authentication + JSON security rules | Amazon Cognito user pools |
| Auth pricing above free tier | Included in Pro up to 100K MAU | $0.0055–$0.0055/MAU (Tier 1, 50K–100K band) | $0.015/MAU (Essentials, new default) |
| Realtime sync | Postgres CDC + Broadcast (binary payloads since July 2026) | Native Firestore/Realtime DB listeners | AppSync GraphQL subscriptions |
| Vector/AI search | pgvector extension, native SQL | Vector search via Google Cloud AI integrations | No native vector store (requires OpenSearch/Bedrock add-on) |
| File storage cost | Bundled in Pro egress allowance | $0.026/GB stored, $0.12/GB downloaded | $0.023/GB stored, $0.15/GB served (Amplify Hosting) |
| Serverless functions | Edge Functions (Deno-based) | Cloud Functions 2nd gen, $0.40/million invocations | AWS Lambda via Amplify backend |
| Compliance tier | SOC 2 + ISO 27001 on Team ($599/mo) | Google Cloud compliance inherited | AWS compliance inherited (broadest catalog) |
| GitHub stars | 103,192 (supabase/supabase, May 2026) | 5,122 (firebase-js-sdk, May 2026) | Not directly comparable (spans multiple AWS repos) |
| SDK weekly npm downloads | ~19.8M (@supabase/supabase-js) | ~7.3M (firebase) + ~6.2M (firebase-admin) | Bundled with broader aws-amplify package family |
| Self-hosting option | Yes, fully open source | No | Partially (Amplify CLI is open source; backend runs on AWS) |
| Latest 2026 update | Realtime binary payloads, MongoDB FDW (July 2026) | JS SDK 12.17.1 (Aug 4, 2026), Apple SDK 12.18.0 (Aug 19, 2026) | Gen 2 infrastructure-as-code DX, ongoing 2026 updates |
The pattern that jumps out immediately: Supabase bets everything on Postgres being good enough for 95% of apps, Firebase bets on its NoSQL document model being fast enough to not need SQL, and AWS Amplify bets that teams already inside AWS will pay a premium for native integration with Cognito, AppSync, and DynamoDB. None of these bets are wrong — they just serve different teams.
Database Architecture: Postgres, Firestore, and DynamoDB
Supabase’s core differentiator is that it isn’t really a proprietary database at all — it’s a managed PostgreSQL instance with a REST and realtime layer bolted on top via PostgREST and its Realtime engine. That means anything you already know about relational schemas, joins, foreign keys, and transactions carries over directly. You get real SQL, real migrations, and the entire Postgres extension ecosystem, including PostGIS for geospatial data and pgvector for embeddings.
Firebase runs on two separate NoSQL stores: Cloud Firestore, a document database organized around collections and documents, and the older Realtime Database, a JSON tree synced in near real time. Firestore is the default choice for new projects because it scales better and supports richer queries, but neither store supports joins or complex relational queries the way Postgres does. Developers denormalize data heavily to avoid N+1 query patterns, which works well for read-heavy mobile apps but gets awkward fast for reporting or analytics workloads.
AWS Amplify Gen 2 defaults to DynamoDB, provisioned and wired up automatically through AppSync’s GraphQL layer when you define a data model in Amplify’s TypeScript schema files. DynamoDB is a key-value and document store built for massive horizontal scale, and it’s what powers some of Amazon’s own highest-traffic systems. The tradeoff is the same one Firestore users face: no native joins, careful key design required upfront, and query patterns that need to be modeled before you write code, not after.
For teams that already think in SQL, or that need ad hoc reporting queries without standing up a separate data warehouse, Supabase’s Postgres foundation is the clear structural advantage. For teams building mobile-first apps with offline sync as a hard requirement, Firestore’s client SDKs remain the most mature option on the market.
Authentication and Security: RLS vs Security Rules vs Cognito
This is where the three platforms diverge most sharply in philosophy. Supabase Auth issues JWTs and maps them directly into Postgres roles, which means every authorization decision is enforced as a Row-Level Security (RLS) policy written in SQL, inside the database itself. A policy like “users can only see rows where user_id matches auth.uid()” lives next to your schema, not in a separate rules file, and it can’t be bypassed by a client-side bug because the database enforces it regardless of which API path a request takes.
Firebase Authentication is a standalone identity service, and authorization is enforced through Firestore and Realtime Database security rules — a JSON-like expression language evaluated by a hosted rules engine, outside the database itself. It’s powerful and battle-tested across a decade of mobile apps, but rules live in a separate file from your data model and can be easy to get subtly wrong, particularly around nested collections.
AWS Amplify uses Amazon Cognito user pools for identity, which is the most enterprise-oriented of the three. Cognito supports SAML and OIDC federation for enterprise SSO out of the box, advanced threat protection on its Plus tier, and deep integration with IAM roles for fine-grained AWS resource access. That enterprise depth comes at a real cost, though: Cognito’s 2026 pricing restructured into three tiers — Lite, Essentials, and Plus — and the free allowance dropped from a legacy 50,000 MAU on older grandfathered pools to just 10,000 MAU on new pools.
On raw security architecture, Supabase’s database-native RLS is arguably the hardest to accidentally misconfigure, because the enforcement point is the same layer that stores the data. Cognito is the deepest if your compliance requirements include enterprise SSO and adaptive threat detection. Firebase sits in between: simple to start, but rules complexity grows non-linearly with data model complexity.
Realtime Data Sync and Live Updates
Firebase built its reputation on realtime sync — the Realtime Database was Google’s original answer to “what if your database pushed changes to clients instead of clients polling for them,” and Firestore inherited that DNA with listener-based subscriptions that just work across iOS, Android, and web SDKs with minimal configuration. For chat apps, multiplayer games, and collaborative editors, Firebase’s realtime layer remains the most mature and the least likely to surprise you in production.
Supabase built realtime on top of Postgres’s write-ahead log via logical replication, streaming database changes to subscribed clients over WebSockets. As of the July 2026 developer update, Supabase Realtime Broadcast now supports binary payloads in addition to JSON, a meaningful upgrade for multiplayer and streaming use cases that were previously paying a JSON serialization tax. Because it’s built on native Postgres replication, Supabase’s realtime sync is also the only one of the three where “realtime” and “database” are guaranteed to be perfectly consistent — there’s no separate sync layer that can drift from source-of-truth state.
AWS Amplify handles realtime through AppSync GraphQL subscriptions over WebSockets, billed separately at $2.00 per million real-time update connection-minutes plus $0.08 per million minutes of raw WebSocket connection time. It’s reliable and scales predictably, but it’s also the most expensive of the three on a per-connection basis once you’re past AppSync’s 250,000-operation free tier.
Vector Search and AI-Native Capabilities
This category matters more in 2026 than it did two years ago, because most new backends now need to store and query embeddings for RAG pipelines, semantic search, or recommendation systems. Supabase has the structural advantage here: because it’s Postgres, adding pgvector is just enabling a standard extension, and vector columns live in the same tables as your relational data. You can join a similarity search against user permissions in a single SQL query with RLS enforced automatically — no separate vector database, no data synchronization pipeline between two systems.
Firebase’s vector search story runs through the broader Google Cloud ecosystem rather than being a first-party Firestore feature with its own dedicated branding, which means teams typically end up wiring Firestore to Vertex AI Search or a separate vector index rather than storing embeddings natively alongside documents.
AWS Amplify has no native vector store baked into its default data model. Teams building AI features on Amplify typically bolt on Amazon OpenSearch Service with its k-NN plugin, or route through Amazon Bedrock’s knowledge base feature, both of which are separate services with separate billing and separate infrastructure to manage. For AI-native startups building RAG applications from day one, Supabase’s built-in pgvector support removes an entire category of infrastructure decisions that the other two platforms punt to bolt-on services.
File and Object Storage Compared
Supabase Storage is built on S3-compatible object storage with the same RLS policy engine used for database rows, so file access rules live in the same SQL policy language as everything else. Storage costs are bundled into the Pro plan’s included egress allowance (250 GB) before metered overages kick in.
Firebase Cloud Storage, built on Google Cloud Storage, charges $0.026 per GB stored per month and $0.12 per GB downloaded on the Blaze plan, with 100 GB of downloads included free per month. It integrates tightly with Firebase Authentication for per-user access rules and is the most battle-tested for mobile image and video upload pipelines.
AWS Amplify Hosting bills storage at $0.023 per GB stored and $0.15 per GB served, which undercuts Firebase slightly on raw storage but charges more per GB served. Amplify apps needing user-uploaded file storage typically provision a dedicated S3 bucket through the Amplify Storage category, which follows standard S3 pricing rather than the hosting-specific rate.
Serverless Functions and Edge Compute
Supabase Edge Functions run on Deno at the edge, giving low cold-start latency and direct access to the Postgres database and Supabase Auth context without extra configuration. They’re the newest of the three function runtimes and lean toward simple, focused use cases like webhook handlers, Stripe integrations, and lightweight API endpoints.
Firebase Cloud Functions (2nd gen) run on Google Cloud Functions/Cloud Run underneath, billed at $0.40 per million invocations on the Blaze plan, and support the widest range of language runtimes among the three (Node.js, Python, Go, and more). They’re deeply wired into Firebase Auth and Firestore triggers, making “run this function when a document changes” a one-line configuration.
AWS Amplify backends run on AWS Lambda directly, which means access to the entire AWS Lambda ecosystem — provisioned concurrency, Lambda layers, container image deployments, and every AWS SDK integration that exists. This is the most flexible and the most operationally complex of the three; it’s also the only one where you can, if needed, drop below the Amplify abstraction entirely and manage the underlying Lambda function through standard AWS tooling.
Pricing Breakdown: Free Tiers Through Enterprise
None of these three platforms price the same way, which is exactly why side-by-side comparison matters more than reading any single pricing page in isolation.
| Tier | Supabase | Firebase | AWS Amplify + Cognito + AppSync |
|---|---|---|---|
| Free tier | $0 — 2 projects, 500 MB Postgres, ~50K MAU | $0 (Spark) — 1 GiB Firestore, 10K Auth MAU | $0 for 12 months — 1,000 build min, 5 GB storage, 15 GB transfer, 10K Cognito MAU |
| Entry paid tier | Pro: $25/month flat, 8 GB disk, 100K MAU, 250 GB egress included | Blaze: pay-as-you-go, no flat fee | Pay-as-you-go, no flat fee |
| Build/compute unit cost | Included in Pro; disk/compute add-ons metered above quota | Functions: $0.40/million invocations | $0.01/build minute |
| Database read cost | Included (flat compute, no per-query metering) | $0.03 per 100,000 document reads (after 50K/day free) | DynamoDB read request units, billed separately |
| Database write cost | Included | $0.09 per 100,000 writes (after 20K/day free) | DynamoDB write request units, billed separately |
| Auth cost per MAU | Included up to 100K on Pro | $0/MAU to 50K, then $0.0055–$0.0025/MAU by volume | $0.015/MAU (Essentials, 10K free) |
| File storage | Bundled into Pro egress allowance | $0.026/GB stored, $0.12/GB downloaded | $0.023/GB stored, $0.15/GB served |
| API request cost | Included (PostgREST, no per-call fee) | Included in Firestore read/write pricing | $4.00 per million GraphQL requests (AppSync) |
| Mid tier | Team: $599/month, adds SOC 2 + ISO 27001 | No mid-tier — Blaze scales linearly | No mid-tier — scales linearly with AWS usage |
| Enterprise | Custom pricing, dedicated support | Custom Google Cloud enterprise agreements | AWS Enterprise Support plans, custom pricing |
The structural difference matters as much as any single number: Supabase’s Pro plan is a flat $25/month that absorbs most database operations, while Firebase and AWS Amplify meter nearly everything by the unit. That makes Supabase’s bill far more predictable for budgeting, but it also means Firebase or Amplify can be cheaper at very low, spiky traffic where you’d otherwise be paying for Supabase compute you’re not using.
What a 100,000-User App Actually Costs
List prices only tell part of the story. Here’s a modeled monthly bill for an illustrative mid-size app: 100,000 monthly active users, 20 million database reads, 4 million writes, 50 GB of database storage, 100 GB of file storage, and 200 GB of monthly data transfer. This is a scenario built from each vendor’s published August 2026 list prices — actual bills vary by region, caching, and workload shape.
| Cost line | Supabase | Firebase | AWS Amplify + Cognito + AppSync |
|---|---|---|---|
| Base plan | $25.00 (Pro) | $0 (Blaze has no base fee) | $0 (no base fee) |
| Auth (100K MAU) | Included | ~$275.00 (50K free, 50K @ $0.0055) | ~$1,350.00 (Cognito Essentials, 10K free, 90K @ $0.015) |
| Database reads/writes | Included | ~$8.61 (reads + writes after free daily quota) | Billed separately per DynamoDB request unit (not included below) |
| Database storage (50 GB) | Metered above 8 GB included | ~$7.50 (Firestore Standard, ~$0.15/GB) | Billed separately per DynamoDB GB-month |
| File storage + transfer | Included in 250 GB egress allowance | ~$26.60 (storage + downloads) | ~$32.30 (Amplify Hosting storage + transfer) |
| API/function calls | Included | ~$0.80 (Cloud Functions, modest volume) | ~$96.00 (AppSync, 24M GraphQL ops) |
| Estimated monthly total | ~$25–$90 (base + modest disk overage) | ~$319 | ~$1,478+ (before DynamoDB charges) |
The single biggest driver of the AWS Amplify total is Cognito’s Essentials tier, now the default for new user pools, at $0.015 per MAU. Switching to the Lite tier cuts that line to roughly $495 at this volume, but Lite drops passkey support, email MFA, and several of the auth flows Essentials includes by default — a real tradeoff, not a free lunch. Even at the cheaper Lite tier, AWS Amplify’s identity cost alone still exceeds Firebase’s entire monthly bill in this scenario. Supabase’s flat-rate model is the structural reason its cost stays nearly flat as MAU and read/write volume climb, right up until database disk or compute needs an upgrade beyond what Pro bundles.
At the opposite end of the spectrum — a pre-launch startup with 5,000 MAU, light read/write volume, and under 5 GB of storage — the picture flips almost entirely into free-tier territory. Firebase’s Spark plan covers that workload at $0 as long as Firestore’s daily quotas aren’t exceeded, and Supabase’s Free tier covers it too, provided the 500 MB database limit and weekly-inactivity pause don’t become a problem for a project with real users hitting it daily. AWS Amplify’s 12-month free tier also comfortably covers this scale, with 10,000 free Cognito MAU and modest hosting usage staying inside the included quotas. The cost gap between the three platforms only opens up once an app crosses roughly 50,000–100,000 MAU with meaningful read/write traffic — which is exactly why so many teams pick a platform at the prototype stage without ever modeling what the bill looks like a year later.
Ecosystem, Adoption, and Release Cadence
Firebase has the decade-long head start and it shows in raw scale: the `firebase` and `firebase-admin` npm packages combine for roughly 13.5 million weekly downloads as of late May 2026, and Google ships SDK updates on a near-monthly cadence — the JavaScript SDK hit version 12.17.1 on August 4, 2026, and the Apple SDK reached 12.18.0 on August 19, 2026.
Supabase is younger but growing fast on GitHub specifically: the core supabase/supabase repository crossed 103,192 stars and 12,575 forks by May 2026, and @supabase/supabase-js pulled roughly 19.8 million npm downloads in a single week that same month — a sign that open-source developer mindshare has shifted meaningfully toward Supabase even though Firebase still leads on total production deployments. Supabase’s July 2026 developer update shipped binary Realtime payloads and a MongoDB foreign data wrapper in Wrappers v0.6.2, both signs of a platform still shipping core infrastructure features at a fast clip rather than settling into pure maintenance mode.
AWS Amplify doesn’t publish a single comparable star count because Gen 2 spans multiple underlying AWS services and open-source libraries rather than one monolithic SDK repo. Its adoption signal is instead the breadth of the AWS ecosystem it plugs into — every Amplify backend is, underneath, standard Cognito, AppSync, DynamoDB, and Lambda resources that any AWS engineer already knows how to operate, monitor, and scale.
Real-World Use Cases: Where Each Platform Wins
Six scenarios where the right pick isn’t obvious until you look at the actual workload, the team’s existing skill set, and the compliance box that has to get checked before launch.
AI startup building a RAG chatbot. Supabase wins outright here. Storing embeddings via pgvector next to the relational data that powers the rest of the app means one database, one RLS policy layer, and no separate vector store to keep in sync. A team can ship a working retrieval pipeline in an afternoon by writing a single SQL function that does similarity search and joins against a permissions table in the same query — something that takes a separate OpenSearch or Vertex AI deployment on the other two platforms.
Consumer mobile app needing rock-solid offline sync. Firebase remains the safer default. Firestore’s offline persistence and conflict resolution have been battle-tested across millions of production apps for the better part of a decade, and the iOS/Android SDKs are the most mature of the three. A team building a note-taking or field-service app that has to work reliably on spotty airport Wi-Fi or in a warehouse basement is taking on real risk by picking a less-proven offline layer just to save on per-operation fees.
Enterprise SaaS already standardized on AWS. AWS Amplify is the pragmatic choice when your compliance team already has AWS Organizations, IAM, and VPC policies locked down. Provisioning Cognito and DynamoDB through Amplify keeps everything inside the same audit boundary rather than adding a third-party vendor to a SOC 2 scope that’s already painful to maintain. Security reviews move faster when the new backend inherits controls the auditors have already signed off on.
Multi-tenant B2B SaaS with row-level data isolation requirements. Supabase’s RLS model maps almost one-to-one onto multi-tenant access patterns — “tenant_id matches the caller’s org” is a single SQL policy, enforced at the database layer regardless of which API surface a request comes through. That matters because a bug in application code that forgets to filter by tenant still can’t leak another customer’s rows; the database itself refuses the query.
Real-time multiplayer game or collaborative whiteboard. Firebase’s Realtime Database still has the lowest-friction path for simple key-value sync at high frequency, though Supabase’s new binary Broadcast payloads have narrowed that gap meaningfully for teams already on Postgres. For a small indie studio shipping a fast prototype, Firebase’s SDK still requires the least boilerplate to get cursor positions or game state syncing across clients.
Regulated fintech or healthtech app needing SOC 2 and audit trails from day one. This is a genuine toss-up between Supabase Team ($599/month, SOC 2 and ISO 27001) and AWS Amplify riding on an existing AWS compliance program. Teams with no prior AWS footprint often find Supabase Team faster to get through a security review because the compliance scope is smaller and the vendor relationship is singular, while teams already deep in AWS get more value from Amplify’s inherited IAM and CloudTrail auditing.
Developer Experience and Local Tooling
Local development workflow ends up mattering as much as any pricing line once a team is actually shipping code every day. Supabase ships a CLI that spins up the entire stack — Postgres, Auth, Storage, Realtime, and Edge Functions — in Docker containers on a developer’s laptop, so schema migrations, RLS policy changes, and function deploys can all be tested locally before touching a hosted project. Because it’s the same Postgres engine locally and in production, there’s no drift between what a developer tests and what ships.
Firebase’s answer is the Firebase Local Emulator Suite, which emulates Firestore, Realtime Database, Auth, Functions, and Hosting locally with a web-based inspection UI. It’s mature and well documented, and it’s genuinely useful for testing security rules against realistic traffic before deploying. The tradeoff is that the emulator is an approximation of the hosted service rather than the literal same engine, so a handful of edge cases in query behavior or index requirements only surface once code hits the real Firestore backend.
AWS Amplify Gen 2 introduced a cloud sandbox model rather than a fully local emulator: ampx sandbox spins up an isolated, personal cloud backend per developer, deploying real Cognito, AppSync, and DynamoDB resources scoped to that individual. It’s faster to get an accurate picture of production behavior since nothing is emulated, but it means every developer is provisioning real (if small) AWS resources just to write code, and local-only development without any cloud connectivity isn’t really supported the way it is with Supabase’s Docker-based CLI or Firebase’s emulator suite.
Reliability and Enterprise Readiness
All three vendors publish status pages and operate on the underlying reliability of a hyperscale cloud, but they don’t offer the same guarantees. Firebase and AWS Amplify both inherit the SLA structure of their parent clouds — Google Cloud and AWS respectively — which means enterprise buyers can point to an existing master service agreement and a well-understood escalation path when something breaks. That inherited maturity is one of the strongest arguments for choosing either platform in a regulated industry where procurement teams need a long incident-response track record on file.
Supabase is younger as an independent infrastructure vendor, and while its core is standard PostgreSQL — arguably the most battle-tested open source database in existence — the managed control plane, connection pooling layer, and Realtime service are Supabase-operated rather than inherited from a decades-old hyperscaler SLA. For teams that need the fastest possible security review, Supabase’s Team tier bundling SOC 2 and ISO 27001 closes much of that gap on paper, but a compliance team doing real diligence will still want to see the vendor’s own incident history and status page track record rather than assuming parity with AWS or Google Cloud by default.
Migration Guide: Moving Between Platforms
Migrating a production backend is never trivial, but the path differs sharply depending on direction.
Firebase to Supabase
This is the most common migration direction in 2026, usually driven by cost predictability or a desire for SQL. The core challenge is schema translation: Firestore’s denormalized document collections need to be flattened into relational tables with explicit foreign keys, which typically means redesigning the data model rather than a mechanical field-by-field copy. Auth migration requires re-issuing user sessions since Firebase Auth tokens and Supabase JWTs aren’t interchangeable — most teams run a dual-auth period where both systems verify sessions during the transition window. Community-built tools exist to export Firestore collections to JSON and import them into Postgres tables, but expect to hand-write the schema and RLS policies rather than relying on a fully automated converter.
Firebase or Supabase to AWS Amplify
This move is typically driven by enterprise procurement requirements rather than technical preference. Amplify’s Gen 2 schema definition (in TypeScript) needs to be written to match your existing data shape, and DynamoDB’s single-table design patterns often require more upfront data modeling work than either Firestore or Postgres. Cognito user import supports CSV-based bulk migration for user records, though password hashes generally can’t be migrated directly — most teams force a password reset flow for the first login post-migration, or run both identity providers in parallel using a federation bridge.
General migration checklist
- Export current data in the most granular format available (Firestore: JSON export per collection; DynamoDB: table export to S3; Postgres: pg_dump)
- Redesign the schema for the target database’s data model — don’t attempt a 1:1 field mapping between relational and NoSQL
- Stand up authentication on the new platform and run a dual-auth verification period before cutting over
- Migrate file storage objects and update all signed URL generation logic to the new provider
- Rewrite security rules or RLS policies from scratch — treat this as a security review, not a copy-paste task
- Run the new backend in shadow mode against production traffic before the final cutover
Pros and Cons
Supabase
Pros: Real Postgres with full SQL access, native pgvector for AI workloads, database-native RLS security, flat and predictable pricing, fully open source with a self-hosting path. Cons: Younger ecosystem with fewer mobile-specific SDK conveniences than Firebase, offline sync is less mature than Firestore, and Postgres schema design requires more upfront modeling than a flexible document store.
Firebase
Pros: The most mature mobile SDKs on the market, best-in-class offline sync, huge community and Stack Overflow coverage after a decade in production, generous free tier for early-stage apps. Cons: No relational queries or joins, per-operation metering that gets expensive at scale, security rules can be error-prone in complex data models, no self-hosting option.
AWS Amplify Gen 2
Pros: Deepest enterprise compliance and IAM integration, unmatched flexibility since it’s built on raw AWS primitives, best choice for teams already standardized on AWS, Cognito supports enterprise SSO out of the box. Cons: The steepest learning curve of the three, Cognito’s 2026 pricing tiers make identity the most expensive line item at scale, no native vector search, DynamoDB single-table design has a real learning curve for teams coming from relational databases.
Supabase vs Firebase vs AWS Amplify: The Verdict
For most new projects starting in 2026 — especially anything touching AI features, multi-tenant SaaS, or a team that already thinks in SQL — Supabase is the strongest default. The combination of native pgvector, database-enforced RLS, and a flat $25/month Pro tier that absorbs most operational costs makes it the platform least likely to produce a surprise bill or a security misconfiguration that only shows up in production.
Firebase remains the right call for consumer mobile apps where offline-first behavior and a decade of battle-tested SDK maturity outweigh the cost of per-operation metering — particularly for apps that won’t hit meaningful scale for a while and can ride the Spark free tier or low Blaze usage for months.
AWS Amplify Gen 2 makes sense specifically for teams already inside the AWS compliance boundary — enterprises that need Cognito’s enterprise SSO, IAM-level access control, and the ability to drop down to raw Lambda and DynamoDB when Amplify’s abstractions aren’t enough. Just budget for Cognito’s Essentials tier carefully; it’s the line item most likely to blow past initial estimates as MAU climbs.
Frequently Asked Questions
Is Supabase actually cheaper than Firebase at scale?
Yes, for most workloads with meaningful auth and database traffic. In the 100,000-MAU modeled scenario above, Supabase lands around $25–$90/month versus roughly $319/month for Firebase, largely because Supabase’s Pro plan bundles auth and database operations into a flat fee instead of metering them per-unit.
Can I self-host Supabase instead of using their cloud platform?
Yes. Supabase is fully open source and can be self-hosted via Docker Compose or Kubernetes, giving teams a path to avoid vendor pricing entirely at the cost of operating the infrastructure themselves. Neither Firebase nor AWS Amplify offers an equivalent self-hosting option.
Does AWS Amplify support offline sync like Firestore?
Amplify DataStore provides offline-first sync with conflict resolution, but it’s generally considered less mature and less widely production-tested than Firestore’s offline persistence, which has been refined across a decade of mobile deployments.
Which platform is best for AI and RAG applications?
Supabase, primarily because pgvector lets you store embeddings in the same Postgres tables as your relational data and query both together in a single SQL statement with RLS enforced automatically. Firebase and AWS Amplify both require bolting on a separate vector search service.
How does Firebase Authentication pricing actually work in 2026?
Tier 1 methods (email/password, phone, anonymous, and prebuilt social providers) are free for the first 50,000 MAU, then scale from $0.0055/MAU down to $0.0025/MAU at higher volume. Tier 2 methods (SAML, OIDC federation) get 50 free MAU, then $0.015/MAU.
Is DynamoDB harder to work with than Postgres or Firestore?
Generally yes, for teams new to it. DynamoDB’s single-table design pattern requires modeling access patterns upfront rather than iterating on schema later, which is a bigger mental shift for teams coming from relational databases than adopting Firestore’s more flexible document model.
Can I switch Cognito pricing tiers to reduce costs?
Yes. Cognito’s Lite tier costs $0.0055 down to $0.0025 per MAU depending on volume, versus $0.015/MAU on Essentials, but Lite drops passkey support, email MFA, and several auth flows that Essentials includes by default. It’s a real feature tradeoff, not just a pricing toggle.
Does Supabase support real relational joins across tables?
Yes, because it’s standard PostgreSQL underneath. You can write arbitrary SQL joins, use foreign keys, run transactions, and apply any Postgres extension — none of which is possible on Firestore or DynamoDB’s NoSQL models.
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