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Name the thing that annoys you before you start shopping. Four irritations account for nearly all of this traffic, they point at four different tools, and one of them points back at Grafana with a config change.
The dashboards are rarely what people want to leave. It is usually the machinery around them.
Four reasons people replace Grafana
Too much to run. Grafana on its own is light, and Grafana alone is useless. You need a data source, which means Prometheus, which means exporters, which means a collector. That is four things to upgrade. Tools that bundle collection and storage and display into one process solve this: Netdata, Zabbix, Checkmk, SigNoz.
Alerting friction. Grafana's unified alerting is capable and its mental model of rules, notification policies and contact points takes an afternoon to learn. If all you wanted was an email when a site goes down, that is a lot of machinery. Uptime Kuma and Netdata solve this in about five minutes each.
Cost at scale. Grafana Cloud bills on active series and ingested gigabytes, which is fine until cardinality grows. Grafana Cloud versus self-hosted has the arithmetic, and the fix is usually self-hosting rather than switching products. Read that one before you rebuild anything.
Wrong tool entirely. A real share of people searching for Grafana alternatives want a BI tool. They have a Postgres database and business questions, and somebody pointed them at a monitoring product. Metabase and Superset are the answer there and it is not a close call.
Kibana and OpenSearch Dashboards
Kibana is the front end for Elasticsearch and the strongest log search interface in open source. Discover, field statistics, KQL filtering, ES|QL for pipe-based analysis and saved searches over full text indexes. OpenSearch Dashboards is the Apache 2.0 fork of it, created from Kibana 7.10.2 in 2021 and now developed under the Linux Foundation's OpenSearch Software Foundation.
What it replaces: Grafana plus Loki, for teams whose logs matter more than their metrics. Where it beats Grafana: searching arbitrary strings across a large log estate, and the depth of the Elasticsearch tooling around it. Where it does not: it reads one backend only, so mixed-source dashboards are impossible, and the free self-managed tier limits notification connectors.
Licence and running it: Elasticsearch and Kibana are available under AGPLv3 since 2024 alongside ELv2 and SSPL, OpenSearch under Apache 2.0. Both want a JVM and real RAM, so budget four to eight gigabytes for a single node before Kibana is in the picture.
Verdict: the right move if log search is your daily work. Grafana versus Kibana has the full comparison, including what each stack costs in memory on one box. It is the wrong move if you picked it to avoid running two services, since the Elastic Stack is more machinery than Grafana with Loki.
SigNoz
SigNoz is an OpenTelemetry-native observability platform that handles traces, metrics and logs in one application, backed by ClickHouse. Point OTel SDKs and collectors at it and you get APM-style service maps, latency percentiles and exception tracking without assembling Prometheus, Loki and Tempo separately.
What it replaces: the whole Grafana plus Prometheus plus Loki plus Tempo assembly. Where it beats Grafana: tracing is a first-class citizen rather than a bolted-on data source, and correlation between a slow span and its logs is built in. Where it does not: the dashboarding is younger and less flexible, the community dashboard library is nowhere near Grafana's, and ClickHouse is another database to understand when tuning gets serious.
Licence and running it: the core is MIT Expat, with an ee/ directory under a separate enterprise licence, as stated in the licence file in the SigNoz repository. Self-hosting is Docker Compose, a Debian and Ubuntu package or a Helm chart. Give it more RAM than you expect, because ClickHouse likes memory.
Verdict: the strongest single-product alternative if you are instrumenting applications with OpenTelemetry and want APM without a per-host bill. Skip it if your monitoring is infrastructure-only, since you would be running ClickHouse to store node metrics that Prometheus handles in a fraction of the footprint.
Uptime Kuma
A self-hosted uptime monitor with a pleasant interface. It checks HTTP endpoints, TCP ports, keywords in a response, DNS records, ping, Docker containers and more, then notifies through 90-plus providers including email, Telegram, Discord and Slack. It ships status pages and certificate expiry warnings too.
It answers up or down, plus response time history. There are no time series and no query language. Adding a monitor is a form.
Licence and running it: MIT, one container, one volume, port 3001. A one-click Uptime Kuma template exists if you would rather not touch Docker at all. The current image carries a :2 tag, so pin it deliberately, and the thing sits happily on the smallest VPS you can rent.
Verdict: if your Grafana instance exists solely to alert on endpoints being down, run this and reclaim an evening a month.
Netdata
Netdata is an agent that installs in one command and immediately gives you per-second metrics with hundreds of auto-discovered integrations and dashboards you did not build. No exporters to pick, no dashboard JSON to import, no query language to learn. It includes machine learning anomaly detection on collected metrics by default.
What it replaces: Grafana plus Prometheus plus node_exporter, for single-server and small-fleet infrastructure monitoring. Where it beats Grafana: time to first useful screen, which is measured in seconds, and per-second resolution that makes short spikes visible where a 15 second scrape interval hides them. Where it does not: dashboards are largely given to you rather than composed, long retention is not its strength, and it does not query your Postgres or your Elasticsearch.
The per-second thing deserves a moment, because it changes what you can see. A CPU spike lasting four seconds is invisible to a 15 second scrape more often than not, so the graph you are staring at during an incident is a smooth line over the exact event you are trying to explain. That is the one capability here I would call genuinely hard to replicate on the Prometheus side without paying for it in storage.
Licence and running it: the Agent is GPLv3 or later, genuinely self-hostable with no account needed. Netdata Cloud is the optional hosted layer for fleet views, with a free Community tier capped at five nodes and restricted to non-commercial use, so read those terms before you build a business process on it.
Verdict: the fastest path from a bare server to real visibility, and my default recommendation for anyone monitoring under ten machines who does not want a stack. Pair it with Prometheus rather than replacing Prometheus if you need long history, since Netdata can export to it.
Zabbix
Zabbix is a full monitoring system in the traditional sense: server, database, web interface, agents, templates, discovery, escalation chains and inventory in one product. It has been shipping since 2001 and it shows in the best way, with template coverage for network hardware and enterprise gear that the Prometheus exporter world has never matched.
What it replaces: the entire Grafana plus Prometheus plus Alertmanager stack, with a proper on-call escalation model included. Where it beats Grafana: SNMP and network device monitoring, agentless checks, multi-level alert escalation, plus a permissions model built for teams that answer to auditors. Where it does not: the visual design is functional rather than pretty, and building an ad-hoc exploratory chart is nothing like as pleasant as Grafana Explore.
Licence and running it: AGPLv3 since version 7.0, which moved it off GPLv2. The Zabbix lifecycle policy ships standard releases every six months with twelve months of support and an LTS roughly every eighteen months carrying five years. That is a genuinely useful promise if you are deploying something you will not touch again soon. It needs MySQL or PostgreSQL behind it.
Verdict: pick Zabbix when you monitor infrastructure you do not control the code of, especially switches, firewalls, load balancers and appliances. Then, if the charts annoy you, keep it and point Grafana at the Zabbix data source through the community plugin, which is a very common ending.
Checkmk and the Nagios lineage
Checkmk grew out of the Nagios world and kept the model of a monitoring server that runs checks against hosts and services and reports a state per service. Adding a host triggers automatic service discovery, so Checkmk finds its filesystems and interfaces for you. Nagios Core makes you write those configuration files by hand.
An aside on names, since it costs people search results. The free edition used to be called Raw Edition and is now called Checkmk Community, so a fair share of the forum threads you find describe a product under a name that no longer exists. Nothing changed but the label.
Licence and running it: the free edition is GPLv2, with Pro, Ultimate, Cloud and MSP editions commercial. Nagios Core itself remains GPLv2 and is still maintained, though I would not start a new deployment on it in 2026 when Checkmk or Zabbix give you discovery for free.
Verdict: the right answer for classic infrastructure estates with a mixed hardware inventory and a compliance requirement to prove every service is checked. The wrong answer for container-native environments, where a per-host check model fights you.
Metabase
Metabase is business intelligence, and a genuine share of Grafana alternative searches want exactly this. You point it at a database, it introspects the schema, and non-technical people build charts through a question builder without writing SQL. Dashboards, scheduled email digests, filters and row-level permissions are all in the free build.
What it replaces: Grafana used as a SQL dashboard tool, which is a real and slightly awkward pattern. Where it beats Grafana: anyone who cannot write SQL can produce a chart, and the semantic layer of models and metrics keeps definitions consistent across dashboards. Where it does not: it is not built for the last five minutes of data, it has no PromQL, and it will not alert you that a server is down.
Licence and running it: source outside the top-level enterprise directory is AGPL, with the enterprise directory under Metabase's commercial licence. Self-hosting is a JAR file or a container. It wants a proper application database rather than the bundled H2 for anything real.
Verdict: if your Grafana instance mostly draws revenue, signups, refunds and queue depth from Postgres, you built a BI tool out of a monitoring tool. Metabase does that job better and your finance team can use it unaided.
Apache Superset
Superset is a Python application that speaks SQLAlchemy, so it connects to nearly any SQL engine. You get a SQL Lab query interface, a chart builder covering dozens of visualisation types and a caching layer for expensive queries. It needs Redis and Celery for that caching and for scheduled reports, and its alerting is report-shaped.
Licence and running it: Apache 2.0, a genuine Apache Software Foundation project with no commercial edition holding features back. Docker Compose for evaluation, Kubernetes or a properly configured Python deployment for production.
Verdict: choose Superset over Metabase when you have analysts who write SQL and want control over the deployment. Choose neither if the question you are answering is "why is this server slow".
Perses
Perses is an open specification for dashboards plus an application that renders them, built GitOps-first so dashboards are versioned resources rather than JSON blobs living in a database. It is the newest entry here and the most interesting one if your objection to Grafana is philosophical.
What it replaces: Grafana as the visualisation layer over Prometheus, in Kubernetes-native setups. Where it beats Grafana: dashboards as code without fighting a UI that wants to own state, a defined dashboard specification, plus a genuinely lightweight footprint. Where it does not: the plugin and community dashboard universe is a fraction of Grafana's, and alerting is not its remit at all.
Licence and running it: Apache 2.0, a CNCF sandbox project. The project site lists plugins for Prometheus, Tempo, Loki, Pyroscope, ClickHouse and others, so the data source story is broader than it was a year ago. Sandbox status means the API can still move, so pin versions.
Where this lands in two years I genuinely do not know. Sandbox projects either grow into the thing everybody uses or quietly stop, and from the outside I cannot tell which one this is yet.
Verdict: worth a serious look if your dashboards live in Git and you already run Prometheus in Kubernetes. Not yet a like-for-like replacement for a mixed estate.
Datadog and New Relic
The commercial answer to "I do not want to run this". Both give you agents, hundreds of integrations, APM with automatic instrumentation, log management and incident tooling behind one login with nothing for you to patch.
The difference between the two of them is billing shape, and that is the thing to compare rather than the feature lists. Datadog bills primarily per host per month with separate line items for logs, APM and custom metrics beyond a per-host allotment. New Relic's pricing page put its free tier at 100 GB of ingest a month and one full platform user when I checked on 26 August 2026, with per-GB pricing above that and a small surcharge for an EU data centre. Both vendors revise those figures regularly.
Which model suits you depends on your shape. Many small hosts with modest telemetry favour ingest-based pricing. Few large hosts producing a lot of data favour per-host pricing. Run your real numbers through both calculators, because the same infrastructure can differ by a factor of three between them.
Verdict: correct for teams under about ten engineers with no infrastructure specialist, and increasingly hard to justify above a few dozen hosts. Grafana versus Datadog works the trade-off against self-hosting through properly, including the custom metrics line that catches people out. Run those numbers before the renewal rather than after it.
Which alternative to pick, and when
For a single VPS or a handful of them, Netdata. It gives you more insight in ten seconds than a Grafana stack gives you in an afternoon, and for small estates the loss of long retention rarely matters.
For a team that has outgrown "is it up" and is instrumenting applications with OpenTelemetry, SigNoz, because tracing is the thing the Grafana stack makes you work hardest for. For a mixed hardware estate with network gear in it, Zabbix wins and it is not close. For a Postgres database and a finance team, Metabase.
For everyone else, the honest recommendation is to stay and fix the specific annoyance. Alerting feels heavy? You are probably fighting notification policies when a single contact point would do. Too many services? Drop Loki and keep metrics only, or swap Prometheus for a single Netdata agent feeding Grafana. Cloud bill climbing? Find the label that exploded your cardinality, since it is nearly always one metric with one bad label. Nothing on this page hands you Grafana's data source breadth or its dashboard library, and rebuilding forty dashboards to escape one config problem is a poor trade.
Licences, for the record, since they are scattered above. Kibana and Elasticsearch are AGPLv3, ELv2 or SSPL, while OpenSearch, Superset and Perses are all Apache 2.0. SigNoz core is MIT Expat and Uptime Kuma is MIT. The Netdata Agent is GPLv3 or later, Zabbix is AGPLv3, Checkmk Community is GPLv2 and Metabase is AGPL outside its enterprise directory.
Before replacing any of it, Grafana versus Prometheus explains what each component in the stack does, which is the confusion sitting under a lot of these searches. The complete Grafana guide takes the install and the day to day operation of it from the beginning.
