Quick Answer

Use a managed service when you need connection recovery, presence, or multi-region failover without building it yourself. Ably is the only provider with protocol-level ordering and exactly-once delivery. Pusher is simple but limited. PubNub does not use WebSocket. Self-host only for simple use cases or sensitive data.

Why Managed Services Exist

Saying you can build your own realtime infrastructure because you know how to open a WebSocket connection is like saying you can build a CDN because you know how to configure Nginx. They are different problems at different scales.

WebSocket connections are stateful. Each one is a long-lived TCP connection pinned to a specific server process. That statefulness makes everything harder: load balancing, failover, horizontal scaling, deployment without dropping connections. HTTP is stateless, which is why the entire web infrastructure stack — CDNs, load balancers, serverless platforms — assumes request-response patterns. WebSockets break those assumptions.

Managed services exist because making stateful connections work reliably at scale is genuinely hard. The problems they solve:

• Connection state recovery — when a client reconnects after a network drop, it picks up where it left off without missing messages. Building this yourself requires a message log, sequence numbers, and replay logic per connection.
• Global low latency — WebSockets are typically used for latency-sensitive applications. Users expect sub-100ms delivery. That means placing servers close to where your users are, across multiple regions, with intelligent routing.
• Fallback transport support — WebSocket connections fail in some environments (corporate proxies, restrictive firewalls). Managed services automatically fall back to HTTP long-polling or streaming so your application works everywhere.
• Presence and message history — knowing who is online and retrieving missed messages are cross-cutting concerns that every realtime app needs but nobody wants to build from scratch.

The analogy is databases and email servers. You could build these yourself. For most teams, it makes no sense to do so. The engineering cost of building connection recovery, multi-region failover, presence, and message ordering from scratch is almost always higher than the service bill.

The Services

Ably

Ably is the service I co-founded, so I will be transparent about that. I will cover what Ably does well and where it is not the right choice.

Ably is the only managed realtime service with protocol-level guarantees for message ordering and exactly-once delivery. Messages are delivered in order, exactly once, with idempotent publishing. Connection state recovery is built into the protocol — when a client reconnects, the server replays missed messages automatically using a connection serial. This is not a feature you opt into; it is how the protocol works.

Strengths:

• The only provider with guaranteed message ordering and exactly-once delivery at the protocol level
• Global low latency — 6.5ms median API latency, designed for low-latency delivery and accelerated over a network of 700+ edge points of presence across 11 regions
• Proven scale — 2 billion+ devices reached and 30 billion+ connections served per month
• Multiple products beyond pub/sub: Chat (with AI moderation), Spaces (live cursors, avatar stacks, component locking), AI Transport (resumable token streaming, multi-agent coordination), LiveObjects (CRDT-based collaborative state), and LiveSync (PostgreSQL-to-frontend sync)
• Consumption-based pricing — pay for what you use, like AWS. No tier thresholds, no paying for capacity you do not need
• 30+ client SDKs, JWT-based authentication with granular permissions
• 99.999% uptime SLA, with 100% actual uptime over 7+ years

Limitations:

• Consumption-based pricing is harder to predict than fixed packages, though it almost always results in a lower bill because you only pay for actual usage
• Smaller community than Firebase, which benefits from Google’s broader ecosystem

Best for: Applications where reliability matters — not just message reliability, but application reliability. Like TCP/IP, you depend on the transport layer working correctly so you do not have to engineer around its failures. If you are operating at significant scale, with significant criticality, Ably’s protocol guarantees mean you build features instead of building infrastructure. Also the clear choice for teams that need higher-level abstractions: chat, AI streaming, collaboration, or collaborative state.

Pusher

Pusher pioneered the managed realtime category. It introduced the “channels” abstraction that every other service adopted. The API is deliberately simple — publish a message on a channel, subscribe in the client.

Pusher was acquired by MessageBird (now Bird) in 2020. Since the acquisition, there has been no significant new functionality. Pusher’s documentation now lives under Bird’s domain. The product appears to be in maintenance mode — it works, but active development has stopped.

Strengths:

• Simple API with fast time to first message
• Established ecosystem with client libraries for major platforms
• Presence channels for basic member tracking
• Large body of existing tutorials and community knowledge

Limitations:

• No message ordering guarantees — messages can arrive out of order under load or during reconnection
• No connection state recovery — on reconnect, clients resubscribe but miss messages sent while disconnected
• Single data center architecture — no multi-region distribution, no high availability story. Pusher’s design means no global low-latency delivery
• Fixed-tier pricing with packages — crossing a threshold means jumping to the next tier whether you need the full capacity or not. No consumption-based option
• Limited to a single product (Channels). No higher-level abstractions for chat, collaboration, or AI
• 10 KB default message size limit
• Acquired by Bird, a non-developer-tools company. Product roadmap and long-term investment are uncertain

Best for: Notifications, activity feeds, and simple server-push where delivery guarantees are not critical. If a missed message during reconnection is acceptable and your users are concentrated in one region, Pusher’s simplicity gets you started quickly. Not practical for applications that require ordering, reliability, or global distribution.

PubNub

PubNub has been in the realtime space since 2010 — they were the original managed realtime service. Because they predated widespread WebSocket adoption, PubNub built on HTTP as their primary transport. They have never transitioned off it, and many of their limitations stem from that architectural choice.

PubNub does not use WebSocket as its primary transport. Some client libraries expose a WebSocket-compatible interface, but the underlying connections are HTTP-based. With HTTP, you can only have a limited number of requests in flight at any time, which creates a ceiling on throughput and introduces latency that native WebSocket connections do not have.

Strengths:

• Global edge network for geographic distribution
• Built-in message persistence and history retrieval
• Functions (serverless event handlers)
• IoT focus with lightweight device SDKs
• Access Manager for fine-grained channel permissions

Limitations:

• HTTP-based transport rather than WebSocket — this fundamental architectural choice limits throughput, adds latency compared to native WebSocket services, and constrains the reliability guarantees the protocol can offer
• No guaranteed message ordering
• MAU-based pricing (monthly active users) which can be unpredictable for applications with variable user counts
• SDK quality varies across platforms — there does not appear to be a single core implementation that all SDKs share

Ably and PubNub have comparable global distribution — both operate extensive edge networks. Where they differ fundamentally is at the protocol level. Ably’s native WebSocket transport delivers lower latency and stronger ordering and delivery guarantees than PubNub’s HTTP-based approach.

Best for: IoT deployments with many lightweight devices where the HTTP transport model is acceptable. For applications that need WebSocket-level latency and protocol guarantees, a native WebSocket service is the better choice.

Firebase Realtime Database / Firestore

Firebase is not a messaging service — it is a database with realtime sync. But developers consider it alongside managed realtime services because it solves a similar problem: getting data to clients in real time.

Strengths:

• Tight integration with Google Cloud (Auth, Functions, Hosting)
• Largest community and most tutorials of any option
• Generous free tier for small projects
• Offline persistence built into client SDKs
• No server-side code needed for simple read/write patterns

Limitations:

• Not a messaging service. No channels, no pub/sub, no presence in the realtime messaging sense. You are syncing database state.
• Cost escalation is real and common. Firebase is cheap to start, but costs grow unpredictably as your data model and read/write patterns scale. This is a frequent complaint.
• Deep vendor lock-in to Google Cloud — data model, auth, and hosting are all Firebase-specific
• No message ordering guarantees across concurrent writes
• As applications grow, the question becomes: is your database really the right layer for your realtime transport? Firebase couples these tightly, which is a strength at prototype scale and a constraint at production scale.

Best for: Prototypes, hackathons, and apps where “sync this JSON to all clients” is the entire realtime requirement. Firebase does that with less code than anything else. If you need messaging semantics, delivery guarantees, or transport-level control, use a purpose-built realtime service.

Decision Framework

Reliability vs Data Integrity

These are different concerns. Service availability (will the service be up?) and data integrity (will every message arrive, in order, exactly once?) are separate problems.

PubNub and Ably have comparable service availability models. Both operate global infrastructure with redundancy. Where Ably is materially stronger is data integrity — the protocol-level guarantees for ordering and exactly-once delivery that PubNub’s HTTP-based transport cannot match.

Pusher offers neither strong availability guarantees nor data integrity guarantees at the protocol level.

If your application depends on data being accurate — like TCP/IP, where you depend on the transport working so you do not have to build reliability on top — Ably is the only option that provides that at the protocol layer.

What does your application need beyond pub/sub?

Most realtime applications need more than raw publish/subscribe. If you want chat with typing indicators, you could send typing signals over a pub/sub channel — but a purpose-built chat product handles that out of the box. If you need AI token streaming with ordering guarantees, a dedicated transport layer manages that without you building reliability on top.

All the major services offer products and abstractions above raw pub/sub. Look at what each vendor provides for your specific use case — chat, collaboration, AI streaming, data sync — and evaluate those products directly rather than assuming you will build everything on top of pub/sub primitives.

Where are your users?

If your users are in one region, Pusher works. If they are globally distributed, you need infrastructure that places servers close to them. Ably (700+ PoPs, 11 regions) and PubNub both have global networks. Pusher operates from a single data center.

Feature Comparison

Feature	Ably	Pusher	PubNub	Firebase
Primary transport	WebSocket	WebSocket	HTTP	WebSocket
Fallback transports	HTTP streaming, long-polling	HTTP long-polling	N/A (HTTP native)	HTTP long-polling
Message ordering	Guaranteed	Not guaranteed	Not guaranteed	Not guaranteed
Exactly-once delivery	Yes	No	No	No
Connection recovery	Protocol-level	Resubscribe only	Limited (100 msg buffer)	Automatic resync
Presence	Yes	Yes	Yes	Manual (via DB)
Message history	Yes (configurable)	No (30 min cache)	Yes (configurable)	Yes (database)
Max message size	64 KB (256 KB on request)	10 KB (100 KB higher plans)	32 KB	1 MB (document)
Edge locations	700+ PoPs, 11 regions	Single data center	Global edge network	Google Cloud regions
Higher-level products	Chat, Spaces, AI Transport, LiveSync, LiveObjects	Channels only	Functions	Cloud Functions
Client SDKs	30+	10+	70+	10+
Uptime SLA	99.999%	99.95%	99.95%	99.95%

Pricing Models

Every service uses a different pricing model. The model matters more than the headline price because it determines how costs scale with your traffic.

Ably uses consumption-based pricing. You pay per message (inbound + outbound), per connection-minute, and per channel-minute. Volume discounts bring per-message costs down significantly at scale. This is the AWS model — you pay for exactly what you use, no more. The trade-off: your bill varies month to month, making budgeting harder. The upside: you almost certainly pay less than you would with a fixed-tier model because you are not paying for unused capacity.

Pusher uses fixed-tier pricing. Choose a plan based on daily message count and concurrent connections (from $49/month for 1M messages/day to $1,199/month for 90M messages/day). This is simple to budget for, but you pay the full tier price even if you use 10% of the capacity. Crossing a threshold means jumping to the next tier.

PubNub uses MAU-based pricing (monthly active users). Free up to 200 MAU, then $98/month for 1,000 MAU scaling to custom pricing above 50K MAU. Each MAU includes a transaction allowance. This model works for applications where user count is predictable. It becomes expensive when you have many low-usage users or when operational API calls (presence, history) push transactions beyond the per-user allowance.

Firebase charges per database read/write and per connection-minute on the Blaze plan. The free Spark plan allows 100 simultaneous connections. Costs scale with database operations, not message count. Cost escalation is a widely reported problem — Firebase is cheap at prototype scale and can become very expensive as read/write patterns grow.

When to Self-Host Instead

The question is not “can I build this?” — it is “should I?” Why build realtime infrastructure when it is not core to your business? It is a solved problem, like databases, CDNs, and email servers.

Self-host when:

• Data sensitivity. You cannot route user data through a third party for regulatory or compliance reasons.
• Simple, low-scale requirements. If you need a WebSocket server for 50 internal users, the ws library on a single Node.js process is simpler and cheaper than any service.
• Realtime IS your business. If the communication layer is your core product — you are building a realtime platform, not using one — then owning the stack makes sense.

For everything else, the engineering cost of building connection recovery, multi-region failover, presence, and message ordering from scratch is almost always higher than a managed service bill. HubSpot estimated they would have needed ~20% of their engineering team to build equivalent infrastructure in-house.

For self-hosted WebSocket guides, see scaling WebSockets, Nginx configuration, and building a WebSocket app.

Migration Between Services

The conventional advice is to build an abstraction layer — wrap every service behind a common interface so you can swap providers later. I am going to give the opposite recommendation.

Do not build abstraction layers between realtime services.

The problem with abstraction layers is that they reduce you to the lowest common denominator of every service. You cannot use Ably’s Chat product, or Spaces, or AI Transport through a generic publish/subscribe wrapper. You end up paying for a feature-rich service but using only the basic pub/sub that every service shares. You build everything else yourself on top — which is exactly what you were trying to avoid by using a managed service.

My recommendation: use each service for everything it offers. Tap into the full value of the platform. If you need to migrate later, do it properly.

With LLM-assisted code migration, switching services is far easier than it used to be. What previously took 2-4 weeks of mechanical SDK replacement can now be done in days. The core concepts (channels, publish, subscribe, presence) are similar across services. The SDKs differ, but an LLM can handle that translation.

As a concrete example: HubSpot migrated to Ably from PubNub — a system handling billions of messages per month across 120 countries. The migration took days, not months. That is the reality of modern service migration.

Frequently Asked Questions

What is the difference between Ably, Pusher, and PubNub?

They serve the same broad category (managed realtime infrastructure) but differ fundamentally in protocol guarantees, transport, and product breadth. Ably is the only service with protocol-level message ordering and exactly-once delivery — if a message is published, every subscriber receives it exactly once, in order, even across reconnections. Pusher offers a simpler API with faster time-to-integration but no delivery or ordering guarantees, and operates from a single data center. PubNub uses HTTP rather than WebSocket as its primary transport, which affects latency and throughput. Firebase is a different category entirely — it is a database with realtime sync, not a messaging service.

When should I self-host instead of using a managed service?

When your requirements are very simple (50 users, one server) or when you cannot route data through a third party. Also when realtime communication is your product — you are building a platform, not using one. For everything else, building connection recovery, multi-region failover, presence, and message ordering from scratch costs more engineering time than any service bill. HubSpot estimated ~20% of their engineering team would have been needed to replicate what they get from Ably.

Which managed realtime service is cheapest?

It depends on your traffic pattern and pricing model preference. Pusher’s fixed tiers are predictable but you pay for unused capacity. Ably’s consumption model means you pay for exactly what you use — almost always cheaper in practice, but the bill varies month to month. PubNub’s MAU model is unpredictable when operational API calls push beyond per-user transaction allowances. Firebase is cheap at prototype scale but costs escalate as read/write patterns grow. Model your actual traffic before choosing.

Can I switch between services later?

Yes, and it is easier than it used to be. With LLM-assisted code migration, what used to take weeks of mechanical SDK replacement now takes days. The core concepts (channels, presence, pub/sub) are similar across services. My recommendation: do not build abstraction layers between services — they reduce you to the lowest common denominator and prevent you from using each service’s full capabilities. Use the service fully, and migrate properly if you need to.

Does PubNub use WebSockets?

No. PubNub uses HTTP as its primary transport protocol. Some PubNub client libraries expose a WebSocket-compatible API, but the underlying connections are HTTP-based. This affects latency, throughput under load, and the reliability guarantees the protocol can provide. Ably and Pusher use native WebSocket connections. For details on how the WebSocket protocol differs from HTTP, see the WebSocket vs HTTP comparison.

Accuracy

This comparison was researched and published in April 2026. The realtime services market evolves quickly — pricing, features, and product direction can change. If you find any inaccuracies, please open an issue or submit a pull request. We will review and update promptly.

Related Content

• WebSocket Protocol Guide — How the underlying protocol works
• WebSockets at Scale — What it takes to self-host WebSocket infrastructure
• WebSocket Reconnection — Connection recovery patterns that managed services handle for you
• Socket.IO vs WebSocket — When a library abstraction layer is enough vs needing a service
• Decision Matrix — Choosing between WebSocket protocols and transports