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etcd vs Frappe

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
Frappe logo

Frappe

Developer Tools

The Python web framework behind ERPNext, sold as managed hosting through Frappe Cloud

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Frappe has a free tier, so it costs nothing to try first.
  • 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.; Frappe the framework is strongly opinionated: its own ORM, templating and job queue mean general Python and Django experience transfers only partly, and onboarding a new developer takes weeks rather than days.
  • They diverge on capability: etcd covers Raft consensus, Frappe covers DocType modelling.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which etcd and Frappe actually diverge.

Attributes where etcd and Frappe differ
AttributeetcdFrappe
Starting priceOn requestFree
Pricing modelopen-sourcePer month by site or server
Free tierNoYes
PlatformsWebWeb, Linux, Docker
CategoryTechnologyDeveloper Tools

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 etcd

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

Only in Frappe

  • DocType modelling
  • Role and field permissions
  • Built-in REST API
  • Background jobs
  • Bench CLI
  • Frappe Cloud hosting
  • App marketplace
  • Multi-tenancy

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 Frappe
  • Leader election and distributed locking in a home-grown scheduler or control plane, using leases and transactionsnot Frappe
  • Service discovery and dynamic configuration where readers need to be notified of changes rather than poll for themnot Frappe
  • Coordinating failover in a clustered database, as Patroni does for PostgreSQLnot Frappe

Frappe

  • A team building an internal business application that needs permissions, audit trail and an API on day one rather than in month threenot etcd
  • An ERPNext user who wants managed hosting, automatic updates and offsite backups without hiring a systems administratornot etcd
  • An Indian or emerging-market business that wants to pay for application hosting in local currency at local price pointsnot etcd
  • A consultancy shipping custom vertical apps to clients on a shared framework with per-client site isolationnot 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.

Frappe

  • The framework is strongly opinionated: its own ORM, templating and job queue mean general Python and Django experience transfers only partly, and onboarding a new developer takes weeks rather than days.
  • The developer pool is small and heavily concentrated in India, so hiring Frappe experience elsewhere is slow and expensive relative to mainstream stacks.
  • Documentation is uneven in depth and lags behind releases in places, so real answers often come from reading the source or the community forum.
  • Major version upgrades of the framework have historically broken custom apps that reach past the DocType layer, so bespoke code carries a recurring maintenance cost at each upgrade.
  • Frappe Cloud recommends against its cheapest Hetzner-backed option for mission-critical production, so the headline $5 entry price is not the price of a production-grade deployment.

Pricing, plan by plan

etcd

On request

No published plan breakdown. See the etcd review.

Frappe

Free
  • Framework, self-hostedFree
    • MIT licensed, no licence fee
    • Install with bench on your own Linux servers
    • You carry updates, backups and security patching
  • Frappe Cloud Sites$5/month
    • Also listed at ₹410 per month
    • Shared servers with 150+ installable apps
    • Automatic updates and offsite backups
  • Frappe Cloud Servers$40/month
    • Also listed at ₹3,600 per month
    • Dedicated or shared virtual machines
    • Unlimited sites on your server

Which should you pick?

Choose etcd if

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

Choose Frappe if

  • You need doctype modelling.
  • You want to start without paying.
  • You work on Web, Linux, Docker.
  • You also want role and field permissions.
Frappe review

Questions people ask

Is etcd or Frappe better?
Neither clearly leads. etcd starts at On request and Frappe at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, etcd or Frappe?
Frappe has a free tier; the other does not. Paid plans start at On request for etcd and Free for Frappe.
Does etcd or Frappe run on more platforms?
etcd runs on Web. Frappe runs on Web, Linux, Docker.
Can I use Frappe for free?
Yes. Frappe has a free tier, so you can try it without paying. etcd starts at On request.
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 Frappe is typically brought in for.
What can etcd do that Frappe cannot?
etcd covers Raft consensus, Linearizable reads, Transactions, Leases. Frappe covers DocType modelling, Role and field permissions, Built-in REST API, Background jobs.

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.

Frappe: Is Frappe the same as ERPNext?

No. Frappe is the framework; ERPNext is the ERP application written on it. You can run Frappe without ERPNext to build your own applications.

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.

Frappe: What licence is the framework under?

MIT, which is permissive and imposes no obligation to publish your changes, unlike the AGPL used by several open source ERP rivals.

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.

Frappe: Can I pay in rupees?

Yes. Frappe Cloud publishes the same plans in Indian rupees, ₹410 a month for sites and ₹3,600 for servers, rather than converting a dollar price at checkout.

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.

Frappe: Do I have to use Frappe Cloud?

No, self-hosting with bench or Docker is fully supported and free. Frappe Cloud is a convenience purchase, and it funds the open source work.

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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