Real-Time Features in SaaS: WebSockets, SSE, or Polling?

You're building your SaaS solo or with a small team, and users start asking for "live updates". They want to see changes without refreshing, get instant notifications, or collaborate in real-time. Sounds simple enough. Then you Google "real-time web features" and fall into a rabbit hole of WebSockets, Server-Sent Events, and conflicting advice about which one to use.

Here's the problem: most technical guides assume you have a dedicated DevOps team and unlimited infrastructure budget. They show you how to architect for millions of concurrent connections when you're trying to figure out if you can afford the extra $50/month in server costs. They explain complex scaling strategies when you're still trying to ship your first version.

The decision between WebSockets, Server-Sent Events (SSE), and polling isn't just technical. It's about choosing infrastructure you can actually manage, costs you can actually afford, and complexity you can actually debug at 2 AM when something breaks. According to research on SaaS scaling challenges, 92% of companies struggle with infrastructure management. For solo founders and small teams without dedicated infrastructure expertise, this percentage is even higher.

So let's see what each approach actually delivers, where they break down, and how to choose based on your specific constraints rather than following the latest tech hype.

Understanding the Real-Time Landscape in 2025

Before diving into specific technologies, you need to understand what "real-time" actually means for your application. A stock ticker updating every second has different requirements than a collaborative code editor where multiple developers edit simultaneously. The technical solution that works for one will be overkill. Or inadequate for the other.

Research shows that 47% of users expect web pages to load in 2 seconds, and 40% abandon sites taking more than 3 seconds. But this performance expectation extends beyond initial page load. Users now expect instant updates: notifications appearing immediately, dashboards reflecting changes without refresh, and collaborative features showing what teammates are doing right now.

The challenge? Traditional HTTP wasn't designed for this, and as a solo founder or small team, you don't have the luxury of over-engineering solutions. You need real-time features that work reliably without requiring a dedicated infrastructure team to maintain them.

Three main approaches evolved to solve this: polling (repeatedly asking), Server-Sent Events (server streaming updates), and WebSockets (bidirectional persistent connections). Each makes different trade-offs between complexity, cost, performance, and capability.

Long Polling: The Fallback Nobody Wants

Let's start with what you probably shouldn't use: long polling. This technique works by having the client send a request to the server, which holds that request open until new data arrives or a timeout occurs. Once the server responds, the client immediately sends another request, repeating the cycle.

Long polling exists primarily as a compatibility fallback for environments that don't support more modern approaches. Some enterprise firewalls with packet inspection struggle with WebSockets, and legacy systems might not support Server-Sent Events. In these rare cases, long polling provides a lowest-common-denominator solution.

But let me be clear: long polling is inefficient by design. Each cycle requires establishing a new HTTP connection with all its overhead, TCP handshake, TLS negotiation, HTTP headers. For a feature checking for updates every few seconds, you're recreating connections constantly. Your server handles these pseudo-persistent requests instead of actual work, and your infrastructure costs reflect this inefficiency.

The numbers don't lie. Performance comparisons show long polling creates significantly higher server load than SSE or WebSockets for equivalent functionality. Each request consumes server resources to maintain the connection, even when no data exists to send. Multiply this across thousands of concurrent users, and you're paying for servers to essentially wait.

When long polling makes sense: legacy system integration where you have no control over infrastructure, enterprise environments with restrictive firewalls that block WebSocket traffic, or temporary backwards compatibility during migration to better solutions. Otherwise, skip it. The other options provide better performance, lower costs, and simpler implementation.

Server-Sent Events: The Underrated Champion

Server-Sent Events represent a standardized way for servers to push updates to clients over a single HTTP connection. Unlike WebSockets, SSE provides exclusively one-way communication from server to client, but for many real-time use cases, that's exactly what you need.

SSE works through the EventSource API, built into all modern browsers. The client establishes a connection, and the server keeps it open, trickling data down as events occur. When the connection drops (network hiccup, server restart, whatever), the EventSource automatically reconnects and picks up where it left off using event IDs.

Here's what makes SSE compelling: it's simple HTTP, which means it works with your existing infrastructure. No special server software required, no protocol upgrades, no fighting with firewalls. Your load balancers, proxies, and CDN already understand HTTP, so SSE connections route through them without special configuration.

The automatic reconnection feature solves one of the biggest pain points in real-time applications. When network conditions change. User switches from WiFi to mobile, tunnel through a spotty connection, whatever. SSE handles reconnection transparently. Your application code doesn't need complex retry logic; the browser handles it.

SSE transmits text-encoded UTF-8 data only, which covers JSON, plain text, and most data formats you'd send in web applications. You can't send binary data, but for notifications, status updates, live dashboards, and most real-time features, text encoding works fine.

Performance characteristics favor SSE for read-heavy scenarios. According to developers who've implemented both, SSE is actually faster than WebSockets for broadcasting because WebSocket's XOR masking adds overhead that SSE avoids. For use cases like live sports scores, news feeds, or system status updates where the server broadcasts to many clients, SSE delivers better throughput than WebSockets.

Where SSE excels: live feeds and news updates where users consume information, progress indicators for long-running operations like file uploads or report generation, server status monitoring and real-time dashboards displaying metrics, notification systems pushing alerts to users, and any scenario where communication flows primarily one direction (server to client).

Real-world example: a project management SaaS showing task status updates. When someone completes a task, marks it blocked, or adds a comment, other team members see updates immediately. The server pushes these events to all relevant clients through SSE connections. Users don't need to send data back through the SSE channel; they use normal API calls for their actions. SSE handles the broadcast of what everyone else is doing.

The limitations show up when you need bidirectional communication. While you can combine SSE with regular AJAX calls. SSE for server-to-client updates, AJAX for client-to-server actions, which creates two separate communication channels you need to coordinate. For truly interactive features where clients and servers exchange messages rapidly, WebSockets provide better architecture.

Connection limits matter for SSE. Browsers typically allow six concurrent HTTP connections per domain, and each SSE connection consumes one. If your application needs multiple real-time streams (chat, notifications, activity feed), you might hit these limits. Solutions exist (HTTP/2 multiplexing, domain sharding), but they add complexity.

Server-side implementation requires keeping connections open, which affects how you architect your backend. Traditional request-response frameworks often struggle with long-lived connections. You need server software designed to handle many concurrent connections efficiently: Node.js, Go, or async Python frameworks work well. Apache or traditional PHP setups struggle.

WebSockets: The Full-Duplex Powerhouse

WebSockets establish a persistent, bidirectional connection between client and server that remains open for the duration of the session. After an initial HTTP handshake to negotiate the upgrade, the protocol switches to WebSocket, enabling both parties to send messages at any time without request-response overhead.

This full-duplex communication makes WebSockets the go-to choice for interactive real-time features. Chat applications, collaborative editing, multiplayer games, real-time trading platforms (scenarios where both client and server need to initiate communication frequently benefit from WebSockets' architecture.

The performance advantages come from maintaining a single persistent connection. No repeated connection establishment, no HTTP header overhead on every message, no latency from polling. Once the WebSocket connection exists, messages flow with minimal overhead in both directions.

WebSockets support both text and binary data, making them versatile for any data type. Sending images, video frames, or binary protocols? WebSockets handle it. This flexibility matters for applications that need to transmit different data formats efficiently.

The RFC 6455 WebSocket standard ensures broad support across all modern browsers and platforms. Whether your users access your SaaS through Chrome, Firefox, Safari, or Edge, WebSockets work consistently. Mobile applications, desktop clients, and web interfaces all support WebSocket connections.

However, WebSockets demand more from your infrastructure than SSE. Maintaining persistent connections for thousands of concurrent users requires servers capable of handling many connections efficiently. Traditional web servers designed for short-lived request-response cycles struggle with long-lived WebSocket connections.

Connection management becomes your responsibility. Unlike SSE's automatic reconnection, when a WebSocket connection drops, you need code to detect the disconnect and re-establish the connection. Many developers use libraries like Socket.IO that handle reconnection logic, heartbeat pings, and fallback mechanisms, but this adds dependencies and complexity that solo founders need to manage carefully.

Some enterprise firewalls inspect packets and struggle with WebSocket traffic, particularly older models like Sophos XG Firewall, WatchGuard, and McAfee Web Gateway. While most modern networks handle WebSockets fine, enterprise environments sometimes require configuration changes or fallback mechanisms.

Scaling WebSockets introduces architectural considerations that simpler approaches avoid. When you eventually run multiple server instances behind a load balancer, maintaining WebSocket connections gets complicated. Solutions exist (sticky sessions, shared state through Redis, dedicated WebSocket gateways), but each adds complexity. For small teams, this might not matter initially, but it's worth understanding before you commit to WebSockets.

Where WebSockets shine: chat applications where users send and receive messages in real-time, collaborative tools like document editors, whiteboards, or design applications where multiple users interact simultaneously, and any scenario requiring true push-pull communication patterns where both client and server initiate frequent messages.

Consider a collaborative design tool like Figma. When one designer moves an element, everyone else sees it immediately. When another designer adds a comment, it appears instantly. Multiple users interact continuously, with both sending and receiving data. WebSockets provide the infrastructure for this kind of tightly synchronized collaboration.

For most small SaaS products, though, communication patterns are simpler. A project management tool doesn't need WebSocket's full capabilities. SSE handles task updates and notifications perfectly well. A CRM doesn't need persistent bidirectional connections for most features. Know your requirements before adopting the more complex solution.

The Cost Reality for Small Teams

Here's what the technical comparisons skip: infrastructure costs matter differently when you're bootstrapped or running on a tight budget. Real-time features aren't just engineering decisions; they're ongoing operational expenses that come directly out of your runway.

Long polling hammers your infrastructure unnecessarily. Every client constantly creates and tears down connections, consuming CPU cycles for connection management rather than productive work. For a solo founder running on a basic VPS or small cloud instance, this inefficiency translates to either degraded performance or needing to upgrade your server tier sooner than necessary.

SSE connections require less server overhead than WebSockets because they're unidirectional and simpler to manage. Your server maintains open HTTP connections, but it doesn't need to track state for bidirectional communication. For a small SaaS with hundreds or low thousands of users, SSE often runs comfortably on infrastructure you're already paying for.

WebSocket costs depend heavily on your architecture and user count. Maintaining persistent connections requires memory and connection-handling capacity. If you're running on a $20-50/month server, adding WebSockets might push you to the next tier. The question becomes: does your feature actually need WebSockets' capabilities, or would SSE work fine while keeping your costs lower?

Cloud provider pricing models matter more when you're watching every dollar. Most infrastructure costs scale with compute resources, but some charge for data transfer. Understanding your cloud provider's pricing structure helps model actual costs before you commit to an approach.

For context, even successful SaaS companies report that connection handling efficiency significantly impacts their scaling costs. The difference between efficient and inefficient real-time architectures can mean doubling your infrastructure costs, a difference between $100/month and $200/month might not matter to a venture-backed company, but it matters when you're bootstrapping.

The smart approach? Start with the simplest solution that works, monitor your costs, and optimize when you have real data about usage patterns. Over-engineering for scale you don't have yet wastes both time and money.

Making the Right Choice for Your Feature

Rather than asking "which technology is best," ask "what does my feature actually need given my constraints?" The answer depends on your communication patterns, current user base, and crucially for small teams: how much complexity you can realistically manage.

Start by mapping your data flow. Does information primarily flow one direction, or do clients and servers exchange messages frequently? If your feature is mostly about pushing updates to users (notifications, status updates, live feeds), SSE likely provides the simplest solution. If users and servers engage in back-and-forth communication (chat, collaborative editing), WebSockets make sense.

Consider your actual scale, not your imagined future scale. A feature used by dozens or hundreds of users has different requirements than one serving thousands. SSE and WebSockets both scale, but WebSockets require more infrastructure investment upfront. For features with uncertain adoption, starting with SSE provides a simpler baseline you can evolve when you have real usage data showing you need more.

Evaluate your existing infrastructure capabilities honestly. Are you running on a simple VPS, a modest cloud instance, or managed platform like Heroku? Your current infrastructure constrains which approaches work without major upgrades. SSE often runs on infrastructure you already have, while WebSockets might require moving to different server software or configurations.

Think about your debugging capacity. When something breaks at 2 AM and you're the only person who can fix it, simpler architectures mean faster resolution. SSE's straightforward model is easier to debug than WebSocket's stateful connections and complex failure modes. If you don't have 24/7 operations support, this matters more than you think.

Assess your time budget realistically. WebSockets provide powerful capabilities, but they also introduce complexity in connection management, state synchronization, and edge case handling. If you're building this feature solo or with one other developer, SSE's simpler model might deliver faster while preserving your development momentum for other parts of your product.

Consider future requirements, but don't over-engineer for them. Developers often justify WebSockets by saying "we might need bidirectional communication later." Maybe, but premature optimization costs you shipping time now. Start with what solves today's problem simply. You can always upgrade when you have actual data about how people use the feature, and by then, you might have more resources to handle the complexity.

Practical Implementation Patterns

Once you've chosen an approach, implementation patterns help avoid common pitfalls that complicate deployment and operation.

For SSE implementations, structure your server to handle many concurrent connections efficiently. Event-driven frameworks like Node.js, async Python (FastAPI, Tornado), or Go excel at this. Traditional threaded servers that create one thread per connection struggle when you maintain thousands of simultaneous SSE connections.

Keep SSE messages small and focused. Remember that each event sent multiplies across all connected clients. If you're broadcasting to 10,000 users and send a 50KB JSON payload, you're transmitting 500MB of data. Design your event format to send only what changed rather than full state snapshots.

Implement heartbeat mechanisms to detect dead connections. Sometimes clients disconnect without cleanly closing the connection (browser crash, network failure, power loss). Your server thinks the connection remains open, wasting resources. Periodic heartbeat pings let you detect and clean up dead connections.

For WebSocket implementations, libraries like Socket.IO provide production-ready connection management, including automatic reconnection, heartbeats, and fallback transports. While using a library adds dependencies, it handles edge cases that your initial implementation will miss.

Design your message protocol carefully. WebSockets give you complete freedom in what you send, which means you need explicit patterns for different message types, error handling, and state synchronization. A well-defined message protocol prevents the spaghetti code that emerges when different features hack their own message formats onto the same WebSocket connection.

Plan for scaling before you need it. When running multiple server instances, you'll need strategies for routing connections and synchronizing state. Redis pub/sub provides a common solution: each server subscribes to relevant channels, and when any server receives a message worth broadcasting, it publishes to Redis. All servers receive it and forward to their connected clients.

Implement connection limits and rate limiting. Without limits, a single misbehaving client or malicious actor can consume your connection capacity. Set per-user connection limits, message rate limits, and max payload sizes. Monitor these limits and adjust based on legitimate usage patterns.

When to Upgrade Your Approach

Knowing when to evolve your real-time architecture prevents premature optimization while avoiding the pain of outgrowing your initial solution.

You might need to move from polling to SSE when polling creates noticeable server load. Your single server struggling under polling traffic, users complaining about delayed updates despite frequent polling, or your hosting costs increasing just to handle the polling overhead.

SSE to WebSockets migration makes sense when you've added enough client-to-server communication alongside your SSE updates that you're essentially implementing bidirectional communication in a complicated way. If your application has SSE for server-to-client updates plus heavy AJAX calls back to the server, and you're struggling to keep these synchronized, WebSockets might simplify your architecture.

Scaling triggers often reveal architectural limitations. If your SSE implementation struggles as you grow from hundreds to thousands of users, you might need to switch server frameworks or upgrade your infrastructure. Sometimes the right move isn't changing technologies but choosing better implementations of the same approach.

The good news? Most real-time architectures can migrate without rebuilding everything. Your application logic (what data to send, when to send it, who should receive it) remains largely the same. The transport mechanism changes, but the business logic doesn't.

For small teams especially, consider managed services when complexity outgrows your capacity. Services like Pusher, Ably, or PubNub handle connection management, scaling, and reliability for a monthly fee. When maintaining your own real-time infrastructure starts consuming significant development time, paying for managed infrastructure might be the smartest choice. Even if it costs more than self-hosting would.

The Hidden Complexity: Client-Side State Management

Here's what trips up most teams: implementing server-side real-time infrastructure is often simpler than managing client-side state when updates arrive constantly.

When the server pushes an update through SSE or WebSocket, your client code needs to integrate that change into the current application state. This sounds simple until you consider the edge cases: what if the user edited the same data locally? What if they're viewing a detail page for a record that just changed? What if updates arrive faster than the UI can render them?

The challenge multiplies in complex applications. A task management tool receives updates about tasks, projects, users, and notifications simultaneously. Each update might affect multiple UI components. Naively applying each update causes UI flickering and performance problems. Sophisticated approaches batch updates, deduplicate redundant changes, and intelligently merge server updates with local modifications.

Frameworks help. React's state management, Vue's reactive system, or dedicated state management libraries like Redux or MobX provide patterns for integrating server updates. But you still need explicit strategies for conflict resolution, optimistic updates, and handling out-of-order messages.

Missed events create another source of complexity. When a client disconnects briefly (user tunnels through subway, mobile network switches towers), they miss updates the server sent during that window. Rejoining the stream works fine if the server is broadcasting full state, but for incremental updates, you need logic to catch up on missed changes. Event IDs help with this, but implementing proper catch-up logic requires thinking through various disconnect scenarios.

Real-World Decision Framework

When you're actually making this decision for a specific feature, work through this framework:

Start here: Does your feature need bidirectional real-time communication (both client and server send messages frequently, often in rapid succession)? If yes, seriously consider WebSockets. If no, keep evaluating.

Next question: Is the feature primarily about the server pushing updates to clients? If yes, and you don't need bidirectional communication, SSE probably provides the simplest solution. If no, and you don't need real-time at all, reconsider whether you actually need persistent connections. Maybe periodic polling with smart caching works fine.

Scale check: Will thousands of users maintain persistent connections simultaneously? If yes, ensure you have infrastructure designed for connection handling at scale. If no, start simple and scale later when you have real usage data.

Network reliability: Will users access this feature from mobile devices or unreliable networks? If yes, SSE's automatic reconnection provides better out-of-the-box experience. If no, either approach works.

Team capability: Does your team have experience implementing and debugging WebSocket architectures? If no, starting with SSE's simpler model might deliver faster while your team builds expertise. If yes, leverage that experience.

Infrastructure compatibility: Does your existing stack handle long-lived connections well? If no, you might need to introduce new services specifically for real-time features. If yes, extending existing infrastructure likely costs less than adding new components.

Most importantly, validate your assumptions. The feature your product team describes might not need real-time updates as frequent as they imagine. A "live" dashboard that updates every 10 seconds might satisfy users while requiring none of this infrastructure. The truly expensive word in software is "real-time" when you don't actually need it.

The Bottom Line for Solo Founders and Small Teams

Real-time features deliver genuine value, better collaboration, faster workflows, more engaging experiences. But they also introduce operational complexity and costs that matter more when you're running lean.

Server-Sent Events provide the best balance for most features where the server pushes updates to clients. Simple to implement, works with standard HTTP infrastructure, automatic reconnection, and runs on infrastructure you probably already have. Use SSE unless you have specific reasons not to.

WebSockets make sense when you need true bidirectional communication with low latency. Chat systems, collaborative editing, real-time multiplayer features (scenarios where both parties initiate communication frequently. WebSockets provide the right foundation for these use cases, despite the additional complexity and infrastructure requirements.

Long polling exists as a compatibility fallback. If you must support environments that block WebSockets and don't handle SSE properly, long polling provides baseline functionality. Otherwise, skip it, the infrastructure overhead isn't worth it for small teams.

The decision matters less than the implementation quality and your ability to maintain it. A well-implemented SSE solution you can debug and maintain beats a sophisticated WebSocket system that breaks mysteriously at 2 AM. Focus on clean code, proper error handling, thoughtful state management, and monitoring that reveals issues before users complain.

Start with the simplest approach that solves your problem. You can always upgrade later when you have real usage data and actual requirements rather than theoretical concerns. Most successful SaaS products evolve their real-time architecture multiple times as they grow. That's not failure; that's smart iteration based on changing requirements.

For solo founders and small teams especially, avoid the trap of over-engineering for scale you don't have yet. Build what works today, monitor how people actually use it, and optimize when the data tells you to. The features that win aren't those using the fanciest technology. They're the ones that work reliably without consuming all your development time.