Orb vs. Metronome vs. Stigg: Full Breakdown

The Orb vs. Metronome question is a billing decision. Most teams comparing Orb and Metronome are looking for one thing: a way to stop pricing changes from blocking engineering. Both tools handle accurate usage billing: counting what customers use and charging them for it. 

Stigg is a different layer, and architecturally a different kind of system. Billing tells you what happened. Stigg decides what's allowed to happen. It's the runtime infrastructure that makes that decision in the request path, before the bill ever runs.

Stigg’s infrastructure is zero-latency, highly available, deployed close to your application, and engineered to hold up at the scale where billing platforms start handing the problem back to engineering.

Conflating billing and runtime infrastructure is a common architectural mistake that turns a routine pricing change into a multi-quarter engineering project.

Orb vs. Metronome vs. Stigg: At a glance

Choose Stigg if you're an AI-native engineering team that needs runtime control over credits, tokens, and entitlements at scale; Stigg offers the kind of synchronous decision-making that billing platforms weren't built for.

Choose Orb if you need a billing stack with raw event ingestion, pricing simulation, and finance-ready reporting without engineering involvement.

Choose Metronome if you have a dedicated engineering team comfortable owning billing logic end to end, and you’re billing on a single, well-defined usage metric.

A note on the build-in-house option

Before comparing vendors, it’s worth acknowledging the most common alternative: building entitlement logic in-house. Most teams start this way. A few database tables, feature flags, and middleware are often enough to get to market quickly.

The challenge appears as the product and pricing evolve. What worked for 50 customers becomes harder to maintain at 500. Legacy plans accumulate, usage limits expand across products, and pricing changes start requiring engineering work.

The runtime side is where homegrown systems break down at scale. Entitlement checks happen on every feature access, and for AI products, on every model call. These need sub-millisecond decisions in the request path. Concurrency makes it harder. 

Multiple agents consume from the same credit pool simultaneously, multi-dimensional limits run across user, team, and org, and the entitlements service can never block a legitimate request, even during a bad minute.

The system that took a week to build eventually requires a dedicated team to maintain, and a team of three to five engineers on monetization infrastructure is a permanent, seven-figure line item that produces no differentiated product value. That's usually when teams evaluate infrastructure like Stigg.

Meet the contenders

Stigg: Runtime infrastructure for AI usage control and entitlements

Stigg is the usage runtime for AI products. It enforces credit limits, usage caps, and entitlements synchronously, in the request path, before any spend hits the bill. Engineering teams use Stigg for real-time credit, wallet, and token control, per-agent and per-team tenancy, and feature-access enforcement at scale.

Stigg sits above billing as the control plane. It works alongside Stripe, Zuora, Chargebee, and custom billing (not instead of them) and enforces entitlements, credits, and usage limits synchronously in the request path.

Orb: Full-stack usage-based billing

Orb is a usage-based billing platform that handles the full billing lifecycle, from pricing to invoicing and financial reporting. Its raw event architecture lets teams update pricing retroactively without recalculating invoices.

Orb serves SaaS and AI companies that need to experiment with pricing frequently without engineering involvement for every change.

Metronome: Usage metering for engineering teams

Metronome is a usage metering platform designed for engineering teams who prefer to own billing logic directly.

Stripe completed its acquisition of Metronome in January 2026, and has said it plans to integrate Metronome's capabilities into the Stripe Billing platform, so evaluating Metronome today increasingly means evaluating a Stripe-owned billing stack and the roadmap that comes with it.

It handles usage metering, pricing, and contracts, but requires more engineering involvement for setup and iteration than Orb.

Orb vs. Metronome vs. Stigg: Feature breakdown

Entitlements and feature access control

Entitlements in Stigg are commercial allowances that define what a customer can access and how much they can use. That means:

• A customer's effective entitlements are the sum of their active plan, inherited base plans, add-ons, trials, and promotional grants, with the most generous value winning when sources conflict.

• Stigg enforces all of this in real time, with hard limits that deny, soft limits that allow overage and track it, and credit deductions.

• Those limits nest. Stigg's governance engine enforces budgets across an entire hierarchy, including organization, department, team, user, and individual AI agent, and evaluates the full chain on every check, so a request is granted only when every budget above it allows it.

• One usage event updates balances at every level at once, so cost attribution doesn't require reporting usage multiple times, and dimension-scoped sub-budgets let a team hold a broad token budget while a specific model or workload runs on a tighter one. Packaging changes ship without code deploys.

Orb works downstream. It handles billing after usage happens, not access inside the product. It is not an entitlements system.

Metronome meters usage for billing purposes. It was not built to control what customers can actually do inside your product in real time.

Winner: Stigg. Orb and Metronome don't operate in this layer.

Usage metering

• Stigg meters usage for enforcement. It tracks consumption against plan thresholds, enforces credit limits, and triggers hard or soft limits in real time. That metering feeds entitlements enforcement, not invoicing.
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• Orb meters usage for billing. It ingests raw events in real time with no pre-aggregation required. Teams can update pricing retroactively because every event stays stored and queryable.
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• Metronome ingests and retains raw usage events, and can reapply a newly defined billable metric to historical data through a reflow. In practice, reflows are handled as a support request rather than self-serve, so teams are encouraged to define billable metrics before sending usage. 

This makes late-breaking pricing iteration more of a coordinated process than a self-serve one.

Winner: Orb for billing-grade metering. Stigg for enforcement-grade metering. They solve different problems and belong in different parts of the stack.

Pricing experimentation

• Stigg lets product teams manage packaging without code. Entitlement changes go through a centralized catalog. More complex pricing model changes still land with engineering, but plan and entitlement updates propagate to running services through Stigg's real-time sync. No redeploy required.
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• Orb built Simulations for exactly this. Teams test pricing changes against real historical usage data before going live. Finance and product can model scenarios and compare outcomes without writing a line of code.
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• Metronome requires engineering for pricing changes. There is no native simulation tool. Testing a new pricing scenario means external tooling or custom scripts.

Winner: Orb for billing-side experimentation. Stigg for product catalog changes without deployments.

Engineering overhead

• Stigg's Sidecar runs as a Docker container alongside your application, in the same pod or as a shared service in your private network, and serves entitlement decisions from a local in-memory cache with no external dependency.

• Redis-backed persistent caching is available as an option for serverless environments and large container fleets that need cached entitlements to survive restarts and stay shared across instances.

• Cache hits resolve in single-digit milliseconds and misses fetch from Stigg's Edge API at around 100ms, behind a configurable network timeout (10 seconds by default) so upstream latency never cascades into your app.

• If the timeout is exceeded, the Sidecar returns configured default values rather than hanging or retrying.

• If the Stigg API is unreachable entirely, the Sidecar keeps serving decisions from cache. If the cache is also unavailable, it falls back to static defaults you configure.

• Stigg also syncs across your revenue stack (billing, CPQ, CRM, data warehouses), keeping pricing, packaging, and entitlements aligned.

• The Sidecar exposes a gRPC interface, so any language can call it. Node.js applications don't need it at all, as the Node SDK provides the same low-latency checks, local caching, and real-time updates natively in-process.

For instance, Miro hit this overhead as it scaled. Its homegrown pricing and packaging tooling held up until the product portfolio expanded into AI features, tiered packages, and usage-based pricing. At this point, a routine plan launch turned into a multi-month, cross-functional project.

Moving to Stigg, Miro shipped a credit-based AI pricing model in under 6 weeks, made pricing and packaging changes 6x faster, and saved 5,000 engineering hours, while migrating tens of millions of existing subscriptions onto Stigg with no custom scripts and no customer-facing disruption.

• Orb reduces how much engineering touches billing after the initial integration. Pricing logic moves to a visual editor or SQL, so finance and product teams own it without opening a ticket.
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• Metronome asks more of engineering upfront, but for teams that want that, it is a feature. Engineering gets full ownership over billing logic with no platform layer in between.

Winner: Stigg for entitlements infrastructure. Orb for billing agility without engineering dependency. Metronome for engineering teams that want to own the billing layer directly.

Developer control and custom billing logic

• Stigg gives engineers SDKs, APIs, and a Sidecar for entitlements. Engineering teams own the rules. Stigg handles enforcement entirely outside application code.
  
  For example, Webflow rebuilt its pricing and packaging architecture on Stigg, decoupling pricing changes from code deploys. Product managers can now ship most packaging updates (like localization add-ons) without engineering involvement, while more complex pricing-model changes (hybrid pricing, credits, new add-ons) still flow through engineering.
  
  The result: add-on rollouts went from months to about four hours, usage-based pricing from quarters to a few weeks, and roughly 500 engineering hours a year returned to product work, with pricing changes rolling out to millions of customers in a single click.
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• Orb abstracts billing logic through SQL-based metric definitions and a visual editor. That reduces engineering involvement, but it also means less direct control over how billing logic gets built and maintained over time.
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• Metronome gives engineering teams the most direct control of the three. Every step of the pricing and billing workflow is defined by the team.

Native integrations with cloud marketplaces, CRM, and ERP systems are handled through configuration, and ultra-low-latency alerting is built in for fraud and abuse protection.

Winner: Metronome fits engineering teams that want to own billing infrastructure directly rather than delegate it to a platform.

Finance and revenue operations

• Stigg: Stigg provides auditability for credit balances and usage through a ledger-based system. Stigg's Contract Management generates invoices natively — created in draft for finance review, published, and downloadable as PDFs — and it orchestrates invoicing through Stripe or Zuora where teams already run them.
  
  What Stigg deliberately doesn't do is revenue recognition, tax calculation, and financial compliance reporting; those stay with your billing and ERP stack.
  
  
• Orb: Orb includes real-time financial reporting, customizable dashboards, and audit-ready exports. Orb ties every revenue metric directly to usage events, which simplifies reconciliation and forecasting.
  
  
• Metronome: Metronome provides basic reporting. Finance teams typically need to export data into external tools for deeper analysis and reconciliation.

Winner: Orb is the only one of the three built for finance-grade reporting and revenue operations.

Pros and cons: Orb vs. Metronome vs. Stigg

Orb

Metronome

Stigg

Which tool should you choose?

These tools don't compete directly because they don't do the same thing. Stigg controls what customers can access. Orb and Metronome handle how that usage turns into revenue. If you need both, Stigg and Orb are the combination most teams reach for.

Choose Stigg if your architecture catches overages after the fact rather than preventing them. Entitlement checks run in the request path for tokens, credits, per-agent, and per-team limits.

Packaging changes go through the product catalog. Stigg is built for AI workloads, but the same architecture handles the largest, most complex billing scenarios (multi-product, multi-tenant, multi-region) without becoming the latency bottleneck.

Choose Orb if pricing and billing logic have outgrown engineering-in-the-loop for every change. Orb handles raw event ingestion, pricing simulation on historical data, and enterprise billing scenarios like parent-child hierarchies. No code required after the initial setup.

Choose Metronome if your engineering team wants to own billing logic in code and your pricing model is stable enough that direct control is an advantage.

It serves enterprise contracts with commit models across PLG and SLG motions. For AI-native teams pricing on credits, wallets, or per-agent budgets, real-time enforcement still happens upstream of billing.

Final verdict

Orb vs. Metronome is a billing decision. Stigg is runtime infrastructure for usage and entitlements, deployed inside your environment. Most teams end up running both.

Orb is the stronger billing platform of the two. Its raw event architecture, pricing simulation, and finance-grade reporting suit teams that need pricing agility without engineering involvement for every change.

Metronome fits engineering-led teams that want direct control over billing logic and bill on simple, stable usage metrics.

Stigg covers the layer that neither billing tool touches. Stigg sits above billing, where credits, entitlements, and AI usage caps get enforced before a request completes, even at scale. That layer decides what a customer can actually do. Billing decides how the resulting usage gets invoiced.

How Stigg works as the runtime infrastructure for AI products

Stigg is the runtime layer for AI usage and entitlements. It's the synchronous decision engine in the request path, enforcing what each customer is allowed to do before the bill is ever calculated.

• Credit management: Credits come in blocks with their own expiry dates, cost basis, categories (paid vs. promotional), and configurable burn priority. Depletion is configurable too: hard limits deny usage, soft limits let it go negative.
  
  Every transaction lands in an append-only ledger. Credit-backed usage reported through reportUsage returns the updated balance synchronously, before the asynchronous metering pipeline settles, so strict credit enforcement happens inside the request.

• AI usage governance: Usage caps, credit limits, and per-team or per-agent allocations are enforced in real time, so a single user or agent cannot run up unexpected spend before the system catches up. Multi-dimensional limits (org → department → team → user) resolve consistently under concurrency.
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• Entitlements management: Teams define feature access and usage limits through a centralized product catalog, reducing pricing implementation from months to hours.
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• Sidecar architecture: Persistent caching in your cloud delivers single-digit millisecond decisions, with full fallback if the Stigg API is unreachable. Configurable timeouts prevent upstream latency from cascading into your app.
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• Reliability at scale: Uptime SLAs up to 99.99%, multi-region active-passive deployment with automated failover, CDN-delivered edge reads replicated across regions, audit-logged API calls, durable queues, and retries on every integration. Ingestion scales to 1M+ events/sec on BYOC deployments.
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• Built for AI-native teams: Stigg ships an MCP server, a CLI, and agent skills alongside its SDKs, so pricing catalogs, credits, and entitlements can be modeled and operated from the same agentic tooling the team already builds with.

If credits, wallets, tokens, and AI usage are eating engineering capacity, that's a sign the architecture isn't scaling with the business. Explore how Stigg works.

FAQs

1. Are Orb, Metronome, and Stigg direct competitors?

No, Stigg is not a direct competitor. Orb and Metronome are direct competitors in the usage-based billing category, though since Stripe completed its acquisition of Metronome in January 2026, that comparison is increasingly Orb versus the Stripe billing stack.

The core Orb vs. Metronome decision comes down to ownership model: Orb pushes pricing control to finance and product teams through its UI and simulations, while Metronome assumes engineering owns billing logic in code.

Stigg is runtime infrastructure that handles entitlements and feature access control upstream of both.

2. What is the main difference between Orb and Metronome?

The main difference between Orb and Metronome is data architecture. Orb ingests raw usage events and supports retroactive pricing changes, simulations, and the full billing lifecycle.

Both retain raw events, and the practical difference is self-serve iteration. Orb exposes retroactive pricing changes and simulation directly to the user, while Metronome's equivalent backfill (a reflow) is typically coordinated through support, and its pricing workflow assumes more engineering ownership.

3. Does Stigg replace billing systems like Orb or Metronome?

No, Stigg does not replace billing systems like Orb or Metronome. Stigg enforces feature access and usage limits inside the product at the moment of usage.

Billing systems handle revenue recognition, tax, and financial reporting downstream. Stigg integrates natively with Stripe and Zuora, and can also generate and manage invoices itself through Contract Management for enterprise contracts.

4. When do you need an entitlements layer on top of billing?

You need an entitlements layer when billing alone can't enforce what each customer purchased inside your product.

The clearest signal is when pricing changes require code deployments, or when an AI feature meters tokens after the fact rather than authorizing usage before it happens. This leaves a gap where a single user or agent can run up unexpected spend before any system catches up.

5. Can Stigg handle the scale and complexity of large enterprises?

Yes. Stigg serves entitlement checks at p99 under 10ms, ingests up to 1M+ events/sec, and backs it with uptime SLAs up to 99.99% on a multi-region architecture with automated failover. It runs in production at Webflow, Miro, PagerDuty, Upwork, Qlik, Productboard, 8x8, HackerOne, and AI21 Labs.

The Sidecar architecture keeps entitlement checks local and operational even during upstream issues.

Because the product catalog is decoupled from the billing provider, Stigg supports running multiple billing providers side by side and migrating between them without rewriting application-side entitlement logic.