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ConfigCat vs etcd

ConfigCat logo

ConfigCat

Developer Tools

Feature flag service priced per flag and environment with unlimited seats and unlimited monthly active users

From
Free
Free plan
Yes
Full reviewWebsite
etcd logo

etcd

Technology

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

From
On request
Free plan
No
Full reviewWebsite

The short version

  • Only ConfigCat has a free tier, so it costs nothing to try first.
  • Each has a real cost: ConfigCat there is no experimentation or statistical analysis engine, so teams wanting real A/B tests with significance testing must buy and integrate a separate analytics or experimentation product.; 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.
  • They diverge on capability: ConfigCat covers Feature flags and configuration, etcd covers Raft consensus.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which ConfigCat and etcd actually diverge.

Attributes where ConfigCat and etcd differ
AttributeConfigCatetcd
Starting priceFreeOn request
Pricing modelPer month by feature flag and environment countopen-source
Free tierYesNo
PlatformsWeb, API, iOS, Android, Node.js, .NET, Java, Python, GoWeb
CategoryDeveloper ToolsTechnology

Identical on both: user rating (Not yet rated).

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 ConfigCat

  • Feature flags and configuration
  • Percentage rollouts
  • Targeting rules and segments
  • Unlimited seats
  • Global CDN delivery
  • Audit log
  • Public API and webhooks
  • SDKs across languages

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.

ConfigCat

  • A consumer or mobile app with millions of users where per-MAU flag pricing would cost more than the flags are worthnot etcd
  • A team that wants every engineer, product manager and support agent to have a login without paying per seatnot etcd
  • Decoupling deployment from release with percentage rollouts and a kill switch, without buying an experimentation platformnot etcd
  • A small team that needs ten flags permanently and can run indefinitely on the free tiernot etcd

etcd

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

Where each one falls short

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

ConfigCat

  • There is no experimentation or statistical analysis engine, so teams wanting real A/B tests with significance testing must buy and integrate a separate analytics or experimentation product.
  • Pricing by flag count punishes exactly the hygiene you want: the Pro tier caps at 100 flags, so teams that do not aggressively retire stale flags are pushed to the 325 dollar Smart tier for housekeeping reasons rather than growth.
  • The free tier allows only 2 environments, which does not cover the common development, staging and production split, so almost any real deployment starts on a paid plan.
  • It is a smaller vendor than the category incumbents, so enterprise procurement teams will find less depth in compliance attestations, contractual terms and reference architecture than LaunchDarkly offers.
  • Flag evaluation relies on SDK-side caching of a CDN-delivered config, which is fast but means propagation of a change is eventually consistent rather than instant, something to understand before relying on it as an emergency kill switch.

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

ConfigCat

Free
  • Forever FreeFree
    • 10 feature flags
    • 2 environments and 2 products
    • 2 segments
  • Pro$110/month
    • 100 feature flags
    • 3 environments and 3 products
    • Unlimited seats and MAUs
  • Smart$325/month
    • Unlimited feature flags
    • Unlimited environments, products and segments
    • Unlimited seats and MAUs
  • Enterprise$900/month
    • Everything in Smart
    • Enterprise support and controls
    • Unlimited everything on flag counts

etcd

On request

No published plan breakdown. See the etcd review.

Which should you pick?

Choose ConfigCat if

  • You need feature flags and configuration.
  • You want to start without paying.
  • You work on Web, API, iOS, Android, Node.js, .NET, Java, Python, Go.
  • You also want percentage rollouts.
ConfigCat review

Choose etcd if

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

Questions people ask

Is ConfigCat or etcd better?
Neither clearly leads. ConfigCat 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, ConfigCat or etcd?
ConfigCat has a free tier; the other does not. Paid plans start at Free for ConfigCat and On request for etcd.
Does ConfigCat or etcd run on more platforms?
ConfigCat runs on Web, API, iOS, Android, Node.js, .NET, Java, Python, Go. etcd runs on Web.
Can I use ConfigCat for free?
Yes. ConfigCat has a free tier, so you can try it without paying. etcd starts at On request.
What is ConfigCat best used for?
ConfigCat is most often used for a consumer or mobile app with millions of users where per-mau flag pricing would cost more than the flags are worth, a team that wants every engineer, product manager and support agent to have a login without paying per seat, decoupling deployment from release with percentage rollouts and a kill switch, without buying an experimentation platform, a small team that needs ten flags permanently and can run indefinitely on the free tier. Of those, a consumer or mobile app with millions of users where per-mau flag pricing would cost more than the flags are worth and a team that wants every engineer, product manager and support agent to have a login without paying per seat are not what etcd is typically brought in for.
What can ConfigCat do that etcd cannot?
ConfigCat covers Feature flags and configuration, Percentage rollouts, Targeting rules and segments, Unlimited seats. etcd covers Raft consensus, Linearizable reads, Transactions, Leases.

Answered from the vendors’ own pages

ConfigCat: How is ConfigCat priced?

By feature flag, environment and product count. Seats, monthly active users and flag reads are unlimited on every plan.

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.

ConfigCat: Is the free tier usable?

For small projects yes, but at 10 flags and 2 environments it will not cover a dev, staging and production setup.

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.

ConfigCat: Can it run A/B tests?

It can split traffic, but there is no statistics engine. You need a separate analytics tool to decide a winner.

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.

ConfigCat: How fast does a flag change take effect?

SDKs poll and cache, so changes propagate on the polling interval rather than instantly.

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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