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Technology · head to head

Checkmk vs etcd

Checkmk logo

Checkmk

Technology

Comprehensive IT monitoring, open and flexible

From
Free
Rated
-
etcd logo

etcd

Technology

A distributed key-value store using Raft consensus, built for cluster coordination rather than application data.

From
On request
Rated
-

The short version

  • Only Checkmk has a free tier, so it costs nothing to try first.
  • Each has a real cost: Checkmk pricing calculated by service count, not hosts (approximately 30 services per host on average); etcd it is sized for coordination data, not application data: the default backend quota is 2 GB and 8 GB is the documented recommended maximum, and exceeding it puts the cluster into a NOSPACE alarm where it accepts no writes until an operator compacts, defragments and clears the alarm by hand.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Checkmk and etcd actually diverge.

Attributes where Checkmk and etcd differ
AttributeCheckmketcd
Starting priceFreeOn request
Pricing modelsubscriptionopen-source
Free tierYesNo

Identical on both: platforms (Web), user rating (Not yet rated), category (Technology).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Checkmk

Nothing recorded that etcd does not also cover.

Only in etcd

  • Raft consensus
  • Linearizable reads
  • Transactions
  • Leases
  • Watches
  • MVCC revision history
  • Role-based access control
  • Snapshot backup and restore

What people use each for

The jobs each tool is most often brought in to do.

Checkmk

  • Infrastructure monitoringnot etcd
  • System observabilitynot etcd
  • Enterprise compliance monitoringnot etcd

etcd

  • Storing Kubernetes cluster state, which is what the overwhelming majority of etcd deployments are doingnot Checkmk
  • Leader election and distributed locking in a home-grown scheduler or control plane, using leases and transactionsnot Checkmk
  • Service discovery and dynamic configuration where readers need to be notified of changes rather than poll for themnot Checkmk
  • Coordinating failover in a clustered database, as Patroni does for PostgreSQLnot Checkmk

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Checkmk

  • Pricing calculated by service count, not hosts (approximately 30 services per host on average)
  • Professional support limited to 8-10 hours per week on base plans
  • Synthetic monitoring is separate add-on with per-test pricing

etcd

  • It is sized for coordination data, not application data: the default backend quota is 2 GB and 8 GB is the documented recommended maximum, and exceeding it puts the cluster into a NOSPACE alarm where it accepts no writes until an operator compacts, defragments and clears the alarm by hand.
  • Every write is replicated and fsynced before acknowledgement, so cluster performance is bounded by the slowest disk in it; a member on network-attached storage with high fsync latency causes leader elections and cluster-wide latency spikes that look like network problems and are not.
  • Adding members increases availability but reduces write throughput, because each write must reach a larger quorum; you run three or five members for fault tolerance, and increasing capacity means faster hardware rather than more nodes.
  • There is no sharding and no multi-tenancy, so isolating workloads means running separate clusters, each with its own quorum, certificates, backup schedule and upgrade path, and that operational multiplication is often unexpected.
  • Running it yourself is a real job: periodic compaction and defragmentation, snapshot backups you have actually rehearsed restoring, and rotation of both peer and client TLS certificates, none of which happens automatically outside a managed Kubernetes service.
  • Losing quorum is not self-healing; recovering a cluster that has lost a majority means restoring from a snapshot and accepting that everything written since that snapshot is gone, which makes backup frequency a data-loss budget decision rather than a routine setting.

Pricing, plan by plan

Checkmk

Free
  • Community (Self-Hosted)Free
    • No cost, forever
    • Up to ~100 hosts
    • Basic infrastructure monitoring
  • Pro (Self-Hosted)$190/month
    • Advanced analytics
    • Reporting
    • Distributed monitoring
  • Ultimate (Self-Hosted)$275/month
    • Full-stack observability
    • Advanced security compliance
    • 10 hours x 5 days professional support (upgradable to 24/7)
  • CloudAI (SaaS)$240/month
    • Fully managed cloud hosting
    • 99.5% uptime SLA
    • Supports up to 50000 services

etcd

On request

No published plan breakdown. See the etcd review.

Which should you pick?

Choose Checkmk if

  • You want to start without paying.

Choose etcd if

  • You need raft consensus.
  • You also want linearizable reads.

Questions people ask

Is Checkmk or etcd better?
Neither clearly leads. Checkmk starts at Free and etcd at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Checkmk or etcd?
Checkmk has a free tier; the other does not. Paid plans start at Free for Checkmk and On request for etcd.
Does Checkmk or etcd run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Checkmk for free?
Yes. Checkmk has a free tier, so you can try it without paying. etcd starts at On request.
What is Checkmk best used for?
Checkmk is most often used for infrastructure monitoring, system observability, enterprise compliance monitoring. Of those, infrastructure monitoring and system observability are not what etcd is typically brought in for.
What can Checkmk do that etcd cannot?
etcd covers Raft consensus, Linearizable reads, Transactions, Leases.

Answered from the vendors’ own pages

Checkmk: Is there a free version of Checkmk?

Yes, Checkmk Community edition is free forever and supports up to approximately 100 hosts for basic infrastructure monitoring with no cost.

Source
etcd: Can I use etcd as an application database?

No. It is designed for metadata and coordination, with a recommended maximum store size of around 8 GB, no sharding and a write path deliberately optimised for durability rather than throughput. Application data belongs in a database built for it.

Checkmk: How does Checkmk calculate pricing by host count?

Checkmk uses service-based pricing where each monitored aspect (file system, hardware sensor, switch port, metric) counts as one service. On average, there are approximately 30 services per host.

Source
etcd: How many members should a cluster have?

Three for most cases, five where you need to survive two simultaneous failures. Always an odd number, because an even-sized cluster gains no additional fault tolerance while making quorum harder to reach.

Checkmk: What is the difference between Checkmk Pro and Ultimate tiers?

Pro tier at 190 EUR/month includes advanced analytics and 8x5 support, while Ultimate at 275 EUR/month adds full-stack observability, advanced compliance features, and upgradable 24/7 support.

Source
etcd: What happens when the store fills up?

The cluster raises a NOSPACE alarm and stops accepting writes, becoming effectively read-only. Recovery requires compacting old revisions, defragmenting each member and then explicitly disarming the alarm, all done by an operator.

Checkmk: Does Checkmk offer a managed SaaS option?

Yes, Checkmk CloudAI is a fully managed SaaS tier at 240 EUR/month with 99.5% uptime SLA and support for up to 50000 services.

Source
etcd: Why is my etcd cluster slow or unstable?

Almost always disk latency. Because every write is fsynced before acknowledgement, slow or shared storage causes heartbeat timeouts, leader elections and cascading latency. Local SSDs with low fsync latency are effectively a requirement.

etcd: How does it compare with Consul or ZooKeeper?

All three provide consensus-backed coordination. etcd has the simplest data model and the Kubernetes ecosystem behind it; Consul bundles service discovery, health checking and a service mesh; ZooKeeper is older, JVM-based and still common under Kafka and Hadoop-era systems.

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