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Technology · head to head

etcd vs Sourcegraph

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
Sourcegraph logo

Sourcegraph

Developer Tools

Code search and intelligence platform for large codebases with Cody AI assistant

From
$16000/year
Free plan
No
Full reviewWebsite

The short version

  • Each has a real cost: 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.; Sourcegraph enterprise pricing starting at $16k annually creates significant barrier for small teams
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which etcd and Sourcegraph actually diverge.

Attributes where etcd and Sourcegraph differ
AttributeetcdSourcegraph
Starting priceOn request$16000/year
Pricing modelopen-sourcesubscription
PlatformsWebCloud, Self-hosted
CategoryTechnologyDeveloper Tools

Identical on both: free tier (No), 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 etcd

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

Only in Sourcegraph

Nothing recorded that etcd does not also cover.

What people use each for

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

etcd

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

Sourcegraph

  • Large-scale code migrations across hundreds of repositoriesnot etcd
  • Enterprise governance and code ownership trackingnot etcd
  • AI-assisted bug hunting and security pattern detectionnot etcd
  • Onboarding engineers into large unfamiliar codebasesnot etcd
  • Regulatory compliance and code audit trailsnot etcd

Where each one falls short

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

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.

Sourcegraph

  • Enterprise pricing starting at $16k annually creates significant barrier for small teams
  • No free tier or standard plan published; all options require custom sales engagement
  • Complex enterprise-only positioning limits adoption compared to GitHub Copilot's pervasiveness
  • Requires indexing entire codebase; not suitable for small or ephemeral projects

Pricing, plan by plan

etcd

On request

No published plan breakdown. See the etcd review.

Sourcegraph

$16000/year
  • Enterprise$16000/year
    • Scales with team size
    • Credits for AI features per user
    • Deep Search

Which should you pick?

Choose etcd if

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

Choose Sourcegraph if

  • You work on Cloud, Self-hosted.
Sourcegraph review

Questions people ask

Is etcd or Sourcegraph better?
Neither clearly leads. etcd starts at On request and Sourcegraph at $16000/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, etcd or Sourcegraph?
etcd starts at On request and Sourcegraph at $16000/year.
Does etcd or Sourcegraph run on more platforms?
etcd runs on Web. Sourcegraph runs on Cloud, Self-hosted.
What is etcd best used for?
etcd is most often used for storing kubernetes cluster state, which is what the overwhelming majority of etcd deployments are doing, leader election and distributed locking in a home-grown scheduler or control plane, using leases and transactions, service discovery and dynamic configuration where readers need to be notified of changes rather than poll for them, coordinating failover in a clustered database, as patroni does for postgresql. Of those, storing kubernetes cluster state, which is what the overwhelming majority of etcd deployments are doing and leader election and distributed locking in a home-grown scheduler or control plane, using leases and transactions are not what Sourcegraph is typically brought in for.
What can etcd do that Sourcegraph cannot?
etcd covers Raft consensus, Linearizable reads, Transactions, Leases.

Answered from the vendors’ own pages

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.

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.

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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