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ESLint vs etcd

ESLint logo

ESLint

Developer Tools

Find and fix problems in JavaScript code

From
Free
Free plan
Yes
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

The short version

  • Only ESLint has a free tier, so it costs nothing to try first.
  • Each has a real cost: ESLint slow performance on large codebases compared to newer tools like Oxlint and Biome; 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 ESLint and etcd actually diverge.

Attributes where ESLint and etcd differ
AttributeESLintetcd
Starting priceFreeOn request
Pricing modelUnknownopen-source
Free tierYesNo
PlatformsBrowser-based JavaScript, Node.js, Any JavaScript environmentWeb
CategoryDeveloper ToolsTechnology
Founded2019Unknown

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 ESLint

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.

ESLint

  • Statically analysing JavaScript and JSX to find problems before runtimenot etcd
  • Automatically fixing issues with syntax-aware rewritesnot etcd
  • Enforcing a consistent code style across a teamnot etcd
  • Running as a CI step to block non-conforming codenot etcd
  • Writing custom rules for project-specific conventionsnot etcd

etcd

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

Where each one falls short

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

ESLint

  • Slow performance on large codebases compared to newer tools like Oxlint and Biome
  • Complexity in configuration from scratch, particularly for TypeScript support
  • Limited built-in TypeScript support, requiring separate parsers and coordination with new TypeScript features

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

ESLint

Free

No published plan breakdown. See the ESLint review.

etcd

On request

No published plan breakdown. See the etcd review.

Which should you pick?

Choose ESLint if

  • You want to start without paying.
  • You work on Browser-based JavaScript, Node.js, Any JavaScript environment.

Choose etcd if

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

Questions people ask

Is ESLint or etcd better?
Neither clearly leads. ESLint 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, ESLint or etcd?
ESLint has a free tier; the other does not. Paid plans start at Free for ESLint and On request for etcd.
Does ESLint or etcd run on more platforms?
ESLint runs on Browser-based JavaScript, Node.js, Any JavaScript environment. etcd runs on Web.
Can I use ESLint for free?
Yes. ESLint has a free tier, so you can try it without paying. etcd starts at On request.
What is ESLint best used for?
ESLint is most often used for statically analysing javascript and jsx to find problems before runtime, automatically fixing issues with syntax-aware rewrites, enforcing a consistent code style across a team, running as a ci step to block non-conforming code. Of those, statically analysing javascript and jsx to find problems before runtime and automatically fixing issues with syntax-aware rewrites are not what etcd is typically brought in for.
What can ESLint do that etcd cannot?
etcd covers Raft consensus, Linearizable reads, Transactions, Leases.

Answered from the vendors’ own pages

ESLint: Does ESLint automatically fix code issues?

Many problems ESLint finds can be automatically fixed via the --fix flag. ESLint fixes are syntax-aware so you won't experience errors introduced by traditional find-and-replace algorithms.

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.

ESLint: How much does ESLint cost?

ESLint is completely free and open-source software maintained by the OpenJS Foundation. The project accepts voluntary donations from sponsors.

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.

ESLint: Can I write custom ESLint rules?

Yes. You can develop custom rules that work alongside built-in functionality through ESLint's plugin system, allowing complete customization for your project needs.

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.

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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