Supabase real-time Postgres performance vs Firebase myths

Supabase Realtime manages 224,000 messages per second with a 6ms median latency for 32,000 concurrent users. This capacity challenges the idea that managed real-time layers struggle with scale. Even at 80,000 concurrent users and 160,000 channel joins, the system maintains a 46ms median latency. In tests with 50KB payloads, the system handles 28,000 messages per second with 27ms median latency for 4,000 users. Although a community member argued that calling a service serverless is a misnomer because a server always exists, the infrastructure sustains high throughput for 50,000 users even when users per channel reach 100 while maintaining a 19ms median latency. Firebase still leads in mobile-first offline persistence and automatic conflict resolution for native apps.

Postgres Change subscription performance depends on how the database authorizes changes. For 100 users subscribed to a single table, one insert triggers 100 reads. This process creates a bottleneck if the system cannot authorize changes fast enough. The system processes changes on a single thread. Is it possible for the system to handle 50,000 users when channel joins reach 4,000 per second?

Scaling and Costs

Pricing models diverge as workloads grow. Heavy read and write workloads cost 3-5x more on Firebase because it bills per operation. Supabase uses a per-project instance model. This makes costs easier to forecast. For teams needing data sovereignty, self-hosting on an Ubuntu VPS provides alternatives. Pigsty enables the deployment of 576 PostgreSQL extensions, which exceeds the 50 preconfigured extensions found in the cloud version. You can avoid vendor lock-in by using standard PostgreSQL formats. The cost of every new database introduced into an organization is equal to N squared to the cost of the number of databases you already have.

I recommend choosing Supabase if you require predictable pricing. Managed services often limit access to specific extensions due to multi-tenant security challenges. Self-hosting eliminates these restrictions. For production workloads, you should allocate 4 vCPU and 16GB RAM. You can also use external S3 for object storage instead of local Silo to provide an hour-scale recovery path. Supabase storage costs $0.021/GB, whereas Firebase storage costs $0.026/GB. Egress also differs, with Supabase charging $0.09/GB compared to $0.12/GB for Firebase.

The AI Development Paradigm

AI agents require a reactive data plane to stay in sync with human users. Supabase integrates the Model Context Protocol (MCP) server to allow AI agents to query data safely. It also supports branching, which creates an isolated database and API preview for every Git branch. This feature helps teams avoid the complexity of manual environment management. Firebase Data Connect offers a different approach by providing a managed PostgreSQL backend with a GraphQL-like query layer.

The shift to AI-native development changes how we think about data. Developers now act as collaborators who guide AI systems rather than just typing code. Firebase offers Gemini-based assistance through Firebase Studio, while Supabase provides an assistant in its dashboard to generate SQL and RLS policies. Platforms like Devin and Replit operate in restricted domains, but they still struggle with being well-integrated with existing iterative engineering practices. Developers can use vibe coding to create a frontend and database schema to build applications. This transition allows engineers to move from being expert code typists to AI collaborators. I think the winner depends on whether your team wants a single Postgres database or a suite of managed Google services. You should evaluate if your existing workflow relies on the Google ecosystem or open-source flexibility.