Better Stack vs Highlight.io: A Complete Comparison for 2026

Highlight.io built a loyal following by solving a very specific problem extremely well: connecting session replay directly to debugging. Instead of jumping between separate tools for errors, logs, and user sessions, developers could see the replay, console output, network activity, and stack trace together in one timeline. That workflow made debugging dramatically faster.

But there is an important reality behind this comparison now: Highlight.io no longer exists as an independent product.

After LaunchDarkly acquired the company in 2025, Highlight’s technology was folded into LaunchDarkly Observability, and the standalone hosted service was deprecated in early 2026. So anyone evaluating “Highlight.io” today is effectively evaluating LaunchDarkly’s observability offering built on Highlight’s foundations.

That changes the conversation. This comparison looks at Highlight at its best, as the standalone observability platform teams originally adopted, while also acknowledging what the acquisition means for teams evaluating it today.

Better Stack addresses a broader operational problem. It combines logs, metrics, traces, session replay, error tracking, on-call scheduling, incident management, and status pages in one fully managed platform, with volume-based pricing and integrated incident workflows. Instead of focusing primarily on frontend debugging, it covers the entire path from observability to incident response.

If your interest in Highlight was driven by its original open-source and self-hostable model, the community-maintained repository still exists.

But for teams looking for a fully supported, standalone observability platform with modern incident management built in, Better Stack is the stronger long-term choice.

Quick comparison at a glance

Platform architecture

Both platforms share a belief that observability data should be cohesive, not siloed. Where they differ is in how they implement that belief and what they include.

Better Stack: unified observability

Better Stack's architecture runs on three foundations: an eBPF collector that captures telemetry at the kernel level without code changes, a unified data warehouse where logs, metrics, and traces share storage and a single query language (SQL or PromQL), and a single interface where incident context assembles without navigating between products.

Watch how the Better Stack collector deploys and discovers services automatically:

Deploy to Kubernetes and the collector runs as a DaemonSet on each node. HTTP and gRPC traffic between services is captured immediately. Database queries to PostgreSQL, MySQL, Redis, and MongoDB are instrumented without touching a line of application code.

One interface, one query language. When an alert fires, the service map, related logs, metrics, and trace examples appear in the same view. Investigating means running a SQL query, not navigating four different product sections.

Better Stack covers 100+ integrations across all major stacks: MCP, OpenTelemetry, Vector, Prometheus, Kubernetes, Docker, PostgreSQL, MySQL, Redis, MongoDB, Nginx, and more.

Highlight.io: cohesion-first monitoring

Highlight's founders described their core philosophy as "cohesion": the mapping of sessions, errors, and logs across your stack so you get a complete picture of what happened, not fragments from disconnected tools. That philosophy drove a product where clicking an error showed the session replay, the console logs, and the network requests that preceded it. No additional configuration. No manual stitching.

Highlight's architecture was built on ClickHouse for log storage and rrweb for DOM-based session recording. OpenTelemetry powered the tracing layer. The frontend SDK captured everything: mouse movements, clicks, scrolls, form inputs, console logs, network requests, and DOM mutations. For teams that needed to understand not just that a bug happened but exactly what the user was doing when it did, the depth of Highlight's session capture was hard to match.

The open source model was central to Highlight's identity. Teams with strict data residency requirements could run the entire platform in Docker with a handful of commands:

git clone --recurse-submodules https://github.com/highlight/highlight
cd docker
./run-hobby.sh

That's a real differentiator. For teams in regions or industries where sending production data to a SaaS vendor isn't acceptable, self-hosting with full source access is genuinely valuable. The ClickHouse backend meant you could even connect your own analytics queries directly to the log storage layer in self-hosted mode, something no SaaS-only product offers.

What Highlight didn't include: infrastructure monitoring, incident management, on-call scheduling, status pages, or metrics beyond what came through OpenTelemetry traces. If those were requirements, you needed additional tools alongside Highlight. For many frontend and full-stack teams, that tradeoff was worth it. Highlight solved the problem it set out to solve, without trying to be everything.

Session replay

Session replay was Highlight's signature feature and the capability that originally distinguished it from traditional APM tools. Better Stack's session replay is now fully available and architecturally integrated with backend telemetry in a way Highlight's standalone product didn't match.

Better Stack: unified frontend-to-backend replay

Better Stack RUM captures frontend sessions, JavaScript errors, Core Web Vitals (LCP, CLS, INP), and user behavior events. Because it shares a data warehouse with backend logs, metrics, and traces, a slow page load doesn't just appear in the session replay. The backend trace for that request and the infrastructure metrics at the time are all accessible from the same view, with the same SQL query language. What does that mean operationally? When a user files a support ticket saying "checkout was broken," you can pull the session replay, the API trace, and the database query that timed out, all from one query, without switching between products.

Session replay filters by rage clicks, dead clicks, errors, and frustration signals. Playback skips dead time. Sensitive fields are excluded at SDK level to keep PII out of recordings.

Product analytics with auto-captured events lets you define funnels and analyze behavior after the fact, without pre-instrumenting specific events before you knew what questions to ask. How many teams have missed an important user journey because they didn't think to instrument it before launch? Better Stack's auto-capture approach removes that constraint.

Web vitals (LCP, CLS, INP) alert when performance degrades per URL, so a deploy that tanks your Core Web Vitals shows up as an alert before users start complaining.

Website analytics tracks referrers, UTM campaigns, entry/exit pages, and locales in real time. If a traffic spike is coming from a campaign or a viral post, you can correlate it with backend load immediately.

Pricing: $0.00150/session replay, included in the same volume-based billing as logs and metrics. No per-session indexing surprises.

Highlight.io: DOM-fidelity replay with DevTools

Highlight's session replay captured the DOM in high fidelity using rrweb, one of the most mature open source session recording libraries. Shadow DOM and Web Components were supported. Canvas and iframe recording were available. The replay showed exactly what the user saw, frame by frame.

DevTools data in replay. Console logs, network requests (including headers and body), and JavaScript errors were all captured and browsable within the session timeline. You could see the XHR call that returned a 500, watch the UI break in response, and read the console error, all without switching tools.

Error linking. Every session linked to the errors that occurred during it. Every error linked back to the sessions where it appeared. The bidirectional linking was automatic and worked from day one, which distinguished Highlight from tools that treated session replay and error monitoring as separate products with bolt-on integrations.

Privacy controls. Highlight offered granular privacy controls: redacting specific fields, masking input values, and excluding sessions from specific users. For teams handling sensitive data, these were configurable at the SDK level rather than requiring post-processing.

Live mode. Following a user's session in real time was supported, which made it useful for customer support and debugging live issues alongside users.

What Highlight didn't include that Better Stack does: website analytics (UTM, referrers, real-time traffic sources), Core Web Vitals alerting tied to deployment timelines, product funnels with auto-captured events, and backend trace correlation in the same interface rather than as a separate linked view.

Error monitoring

Both platforms treat errors as first-class, not afterthoughts bolted onto a logging product. The architectural difference is in what surrounds each error in context.

Better Stack: Sentry-compatible, AI-native

Better Stack Error Tracking accepts Sentry SDK payloads directly. If your team already runs Sentry instrumentation, migrating means updating an endpoint in your configuration, not rewriting SDK integration across every service.

Full trace context. Each error links to the distributed trace of the request that caused it and to the session replay of the user who was affected. That three-way correlation (error, trace, session) is automatic and doesn't require configuring anything beyond the initial setup.

AI-native debugging. Claude Code and Cursor integration includes pre-made prompts that summarize error context. Copy the prompt, paste into your AI coding agent, and get to resolution without manually reading stack traces.

Cost: $0.000050 per exception. 5 million exceptions per month costs $250, with no base platform fee on top.

Highlight.io: OpenTelemetry-powered, session-linked

Highlight's error monitoring was powered by OpenTelemetry and built on the same cohesion philosophy as the rest of the product. Errors appeared alongside the session replay automatically, and clicking an error from the session view showed every other session where that error had occurred.

Custom error grouping. Highlight allowed defining grouping rules to merge related errors that appeared with slightly different messages, which reduced noise in high-volume environments where the same underlying bug might surface with slightly varying stack frames.

Alerting rules. Customizable alerting on error thresholds, with support for routing to Slack, Discord, PagerDuty, and email. Alert fatigue is one of the biggest complaints about error monitoring tools, and Highlight's configurable rules helped teams focus on what mattered rather than drowning in noise from known issues.

OpenTelemetry first-class. Backend errors instrumented via OpenTelemetry appeared alongside frontend JavaScript errors, with the session context bridging both. For a team running a Next.js frontend and a Go backend, both surfaces reported to Highlight with their errors correlated to the same user session. That cross-surface correlation without configuration was one of Highlight's most compelling qualities for full-stack teams.

What Highlight's error monitoring didn't include: Sentry SDK compatibility (Highlight used its own SDK, meaning migration from Sentry required rewriting instrumentation, not just changing an endpoint), deep infrastructure context alongside errors (no host metrics or Kubernetes pod data correlated with errors), or the AI-assisted debugging workflow that Better Stack built with Claude Code and Cursor prompts. For teams where AI coding tools are central to the debugging workflow, that gap is meaningful.

Log management

Highlight's log management was built on ClickHouse, one of the fastest analytical databases available, and it showed in query speed. Better Stack also runs on ClickHouse under the hood, which means both platforms deliver fast log search. The difference is in query depth and how logs connect to the rest of your telemetry.

Better Stack: SQL-native, 100% searchable

Better Stack logs treats all ingested logs as immediately searchable structured data. There's no indexing tier, no archive-and-rehydrate workflow, and no choosing which logs "matter" before an incident happens. 100% of what you send is searchable, immediately.

SQL queries against logs:

SELECT
  service_name,
  COUNT(*) as error_count,
  AVG(duration_ms) as avg_duration
FROM logs
WHERE level = 'error'
  AND timestamp > NOW() - INTERVAL '1 hour'
GROUP BY service_name
ORDER BY error_count DESC

Build visual charts from those queries and save frequently-used ones as presets:

Pricing: $0.10/GB ingestion + $0.05/GB/month retention. 100GB/month = $15 total.

Highlight.io: ClickHouse-backed log search and alerting

Highlight's log management let teams search and set alerts for logs being written throughout their stack. The platform supported widespread SDK support for log shipping and offered customizable log alerts. Logs correlated with the session replay of the user who was active at the time, which is more than most standalone log tools offer.

Session correlation. A log line that appeared during a user's session could be viewed in context alongside the replay of what that user was doing. That automatic linking was genuine added value for debugging user-facing issues.

ClickHouse performance. Because Highlight ran on ClickHouse, queries over large log volumes were fast. Teams that self-hosted had direct access to the ClickHouse instance and could run custom analytical queries if needed.

Where Highlight's log management came up short: the query interface was filter-and-search based, not SQL. Building custom aggregations, grouping by multiple dimensions, or running analytical queries against log data required jumping to the ClickHouse instance directly (in self-hosted mode) or working around the UI's limitations. There was no PromQL interface for metrics derived from log data.

Distributed tracing

Both platforms built on OpenTelemetry for tracing. Better Stack adds eBPF auto-instrumentation that skips the SDK requirement entirely. Highlight required SDK instrumentation but delivered strong session-to-trace correlation.

Better Stack: eBPF, zero code

Better Stack's APM captures distributed traces at the kernel level. HTTP and gRPC service communication, database queries, and external API calls are traced automatically the moment you deploy the eBPF collector. Watch it in action:

Frontend-to-backend correlation. A slow page load in the session replay traces through the backend microservice chain and database calls without switching products.

OpenTelemetry-native, zero lock-in. Your traces use the OTel format natively. Sending them to a different backend requires changing a configuration file, not rewriting instrumentation. How much would it cost your team to migrate from a proprietary tracing agent today? That migration cost compounds every month you stay.

Highlight.io: OTel-native, session-bridged

Highlight's tracing was built on OpenTelemetry from the start. Backend traces (Go, Python, Node.js, Ruby, Java) correlated automatically with the frontend session that triggered them, creating a full-stack view of each user interaction.

Distributed tracing support. Waterfall views, service maps, and latency distributions were all included. Traces captured the full journey of requests through your services.

Session bridging. The trace context from a backend request linked back to the frontend session, so "this API call was slow" connected automatically to "here's what the user was doing when it happened." That bidirectional link was one of Highlight's most practically useful features for debugging user-reported issues.

OpenTelemetry first-class. Because Highlight's tracing was OTel-native from day one, teams could use any OTel-compatible collector and send data to Highlight without Highlight-specific SDKs for the tracing layer.

What the SDK model meant in practice: for each backend service, you needed to initialize the Highlight SDK and configure it. In polyglot environments (Go services, Python services, and Node.js services running side by side), each language required its own SDK integration and configuration. Better Stack's eBPF approach removes this per-service overhead entirely.

Infrastructure monitoring

This is the category with the clearest gap. Better Stack includes full infrastructure monitoring. Highlight.io did not.

Better Stack: Prometheus-native metrics

Better Stack metrics uses PromQL natively and charges based on data volume with no cardinality penalties. Add high-cardinality tags freely, no billing surprises.

Pricing: $0.50/GB/month for metrics, no cardinality charges.

Highlight.io: no infrastructure monitoring

Highlight was explicitly a web application monitoring platform. Host metrics, Kubernetes resource utilization, pod-level CPU and memory, and infrastructure-level dashboards were not part of the product. Teams using Highlight for application monitoring typically ran Prometheus and Grafana alongside it for infrastructure visibility.

This isn't a criticism. Highlight's scope was intentionally narrower: understand why bugs happen in your web application. It did that exceptionally well without trying to be a general-purpose monitoring platform. But if your team needs a single tool for both application and infrastructure observability, Highlight was never the right choice, and Better Stack is.

Pricing comparison

Highlight's pricing was usage-based with a generous free tier. Better Stack is also volume-based. Both avoid the per-seat and per-host models that make Datadog and New Relic bills unpredictable.

Better Stack: transparent volume pricing

• Logs: $0.10/GB ingestion + $0.05/GB/month retention (all searchable)
• Traces: $0.10/GB ingestion + $0.05/GB/month retention
• Metrics: $0.50/GB/month (no cardinality penalties)
• Error tracking: $0.000050 per exception
• Session replay: $0.00150 per session
• Responders (incident management): $29/month
• Monitors: $0.21/month each

No cardinality penalties, no high-water mark billing, no indexing fees.

Highlight.io: usage-based with free tier

Highlight's free tier was one of the most generous in the market before the acquisition. Paid plans scaled based on the volume of sessions, errors, logs, and traces.

Under LaunchDarkly, the free Developer plan includes 5,000 sessions, 5,000 errors, 10M logs, and 10M traces per month. Paid plans charge $3.50/1K sessions, $0.30/1K errors, $1.50/1M traces, and $1.50/1M logs as observability add-ons on top of the feature management base pricing.

The self-hosted path remains available via the open source repository, which eliminates SaaS costs entirely. For cost-conscious teams willing to manage infrastructure, self-hosting Highlight on commodity hardware was a viable zero-cost option. Better Stack has no self-hosted option.

Cost comparison: 50-service application

Incident management and status pages

These two capabilities clearly separate the platforms. Better Stack built complete products for both. Highlight did not include either.

Better Stack: end-to-end incident management

Better Stack incident management covers the full lifecycle: on-call scheduling, unlimited phone/SMS alerts, escalation policies, AI-powered investigation, Slack-native incident channels, and automatic post-mortems.

Better Stack Status Pages includes public and private pages, custom domains, subscriber notifications via email, SMS, Slack, and webhook, and automatic incident timeline publishing.

Highlight.io: integrations only

Highlight integrated with PagerDuty, OpsGenie, Slack, and Discord for alert routing. It didn't include on-call scheduling, escalation policies, phone/SMS delivery, or status pages. Teams using Highlight for monitoring still needed a separate incident management tool for the operational response side.

AI debugging

Both platforms invested in AI-assisted debugging, though they approached it from different angles. Better Stack focused on autonomous incident investigation and external AI assistant integration. Highlight (and now LaunchDarkly) focused on in-product AI that understands flag and session context.

Better Stack: AI SRE and MCP server

The AI SRE activates automatically during incidents, analyzes your service map, queries logs, reviews recent deployments, and surfaces likely root causes without waiting for you to prompt it.

The Better Stack MCP server connects Claude, Cursor, and any MCP-compatible AI client directly to your observability data. Your AI assistant can run ClickHouse SQL against your logs, check on-call status, acknowledge incidents, and build dashboard queries through natural language.

Highlight.io: in-product AI (now Vega via LaunchDarkly)

Highlight's original AI debugging focused on session context: surfacing why a session ended in an error, and making that context shareable with the team. Under LaunchDarkly, this has evolved into Vega, an AI debugging companion that understands feature flag context alongside telemetry data, connecting what changed in a release with what broke in production.

For teams still on Highlight's original platform, the AI features were more limited: useful for summarizing session context, but not the autonomous incident investigation or external AI client integration that Better Stack provides.

Self-hosting and open source

Self-hosting is where Highlight has a clear, genuine advantage over Better Stack. For teams with strict data residency requirements, regulatory constraints, or a preference for running their own infrastructure, Highlight's open source, Docker-based deployment was a real option.

Highlight.io: full self-hosting

Clone the repo, run the setup script, and the entire Highlight stack runs on your infrastructure. The repository is available at github.com/highlight/highlight and remains open source. Teams that self-hosted got full access to the ClickHouse instance, direct control over data retention, and no dependency on a SaaS vendor for data access.

LaunchDarkly has stated the repository will remain available for community maintenance and critical fixes, but the team's focus has moved to the hosted LaunchDarkly platform. If you self-host Highlight today, you're taking on the maintenance burden of an open source project without the original team actively developing it.

Does your compliance or security posture require on-premises data storage? If the answer is yes and you're evaluating Highlight specifically for that reason, the self-hosted path still exists, but you should plan for increased maintenance overhead compared to a year ago.

Better Stack: optional S3 bucket hosting

Better Stack offers an enterprise option to store telemetry data in your own S3 bucket, giving you data ownership without self-hosting the query and UI layers. This satisfies data residency requirements for many regulated industries without the operational overhead of running the full stack yourself.

Deployment and integration

How quickly can you go from "we decided to try this" to "data is flowing and we're finding bugs"? That timeline matters, especially for teams that have been burned by observability tools that took weeks of SDK work before delivering value.

Better Stack

Better Stack's eBPF collector deploys via a single Helm chart. The collector runs as a DaemonSet on each Kubernetes node, automatically discovering services, capturing HTTP and gRPC traffic, and instrumenting database queries without any code changes. Deploy the chart, wait a few minutes, and your first traces and metrics are flowing.

For teams already running OpenTelemetry collectors, Better Stack integrates natively without requiring eBPF at all:

For log collection, Vector pipelines integrate directly:

Timeline: deploy collector, automatic discovery begins, traces and metrics flowing within minutes. Session replay requires adding the frontend SDK, which is a single script tag or npm package.

Highlight.io

Highlight required SDK instrumentation in each service. The frontend SDK was a single JavaScript snippet that captured everything: sessions, errors, console logs, and network requests. Adding it to a React or Next.js app took minutes.

Backend services needed the Highlight SDK for each language. Go, Python, Node.js, Ruby, Java, and Rust were all supported. Each language had its own SDK initialization pattern, and in polyglot environments, each required separate setup. For teams running 10 services in 5 languages, that's 10 separate SDK integrations before data starts flowing.

The self-hosted path added a third deployment step: running the Highlight infrastructure itself (ClickHouse, object storage for replays, the application backend) before you could send any data to it. For teams with the infrastructure experience to manage this, it was worth the control. For teams without, the managed SaaS tier removed that overhead.

Did Highlight's SDK requirement create friction for backend-heavy teams who just wanted traces without touching application code? Yes, and that's where Better Stack's zero-code eBPF approach removes a real barrier.

Highlight.io's website lists SOC 2, HIPAA, and ISO compliance availability. As a product now under LaunchDarkly, the compliance posture extends to include SOC 2 Type II, GDPR, FedRAMP, and HIPAA inherited from LaunchDarkly's enterprise program.

Better Stack covers SOC 2 Type II, GDPR, SSO via Okta/Azure/Google, SCIM provisioning, RBAC, audit logs, and optional data residency. Enterprise customers get a dedicated Slack channel for support and a named account manager.

The acquisition question

Any comparison of Highlight.io in 2026 has to address the elephant in the room: the product you're evaluating is no longer independently maintained.

Highlight's services deprecated on February 28, 2026. Existing customers needed to migrate their SDK snippets and accounts to LaunchDarkly before March 1, 2026. The migration required updating not just endpoints but SDK initialization patterns, since Highlight's standalone SDK was replaced by the LaunchDarkly observability plugin model. For teams with many services instrumented, that migration was a non-trivial project.

The open source repository remains available for community use and critical fixes. LaunchDarkly's team focuses on integrating Highlight's capabilities into the LaunchDarkly platform, not on evolving the standalone tool. What does "community maintenance" mean in practice? Bug fixes that affect the self-hosted path may take longer to merge. New features that LaunchDarkly ships to its hosted platform won't necessarily appear in the open source repo. Security patches will likely be addressed, but at a cadence set by the community rather than a dedicated team.

What this means for teams evaluating Highlight.io today:

If you want the Highlight experience as it was, the closest thing is LaunchDarkly Observability, which runs on Highlight's technology but is bundled with a feature management platform that has its own pricing model (service connections, MAU) that may not fit teams looking purely for observability tooling.

If you want a standalone observability platform with no feature flagging prerequisites, Better Stack covers the same observability surface (session replay, error monitoring, logs, traces, infrastructure monitoring) with deeper infrastructure capabilities, full incident management, and volume-based pricing that scales predictably with your data.

If Highlight's self-hosting capability was specifically what you valued, that option still exists via the open source repository, but requires planning for increased maintenance burden. Are you prepared to handle security patches, dependency updates, and ClickHouse version management without a dedicated team behind the product? That's a legitimate decision, but it should be made with eyes open.

Final thoughts

Highlight.io succeeded because it understood something important early: observability is more useful when every signal is connected by default. Sessions, errors, logs, and traces in one timeline made debugging dramatically simpler, and that philosophy resonated with developers for good reason.

Better Stack builds on that same idea, but expands it beyond debugging into the entire operational workflow. It combines infrastructure monitoring, logs, metrics, traces, session replay, incident management, on-call scheduling, and status pages in one platform, with eBPF-based auto-instrumentation removing much of the SDK setup and maintenance overhead.

The key difference is not just features, but direction. Highlight’s original appeal was strongly tied to its open-source, self-hostable model, and that path still exists through the community-maintained repository. But the hosted product itself is no longer evolving independently after the LaunchDarkly acquisition.

Better Stack, by contrast, is an actively expanding platform built around full-stack observability and incident response as a single system. Instead of focusing only on debugging applications, it covers the broader reality of operating production infrastructure day to day.

So the decision comes down to what you valued most in Highlight.

If it was self-hosting and open-source control, the repository remains an option.

If it was the idea of connected observability with less operational friction, Better Stack delivers that model at a broader scope and with a clearer long-term platform direction.

You can explore it here: https://betterstack.com

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