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Databases · head to head

etcd vs Qdrant

etcd logo

etcd

Databases

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

From
On request
Free plan
No
Visit etcdFull review
Qdrant logo

Qdrant

Databases

High-performance vector database for similarity search and embedding-based retrieval

From
Free
Free plan
Yes
Visit QdrantFull review

The short version

  • Qdrant is an open-source vector search engine.
  • Qdrant is free; etcd prices on request.
  • Where Qdrant falls short: free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

Only the attributes on which etcd and Qdrant actually diverge.

Attributes where etcd and Qdrant differ
AttributeetcdQdrant
Starting priceOn requestFree
Pricing modelOpen-sourceFreemium
Free tierNoYes
PlatformsWebWeb, Self-hosted, Browser extension, Serverless (coming)

Identical on both: category (Databases).

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 Qdrant

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

Qdrant

  • Retrieval-augmented generation (RAG) backends for LLM applicationsnot etcd
  • Semantic search across large document corporanot etcd
  • Multimodal retrieval (text, images, video) for recommendation systemsnot etcd
  • Similarity-based product or content recommendationsnot etcd
  • Real-time vector indexing for streaming embedding datanot 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

Qdrant

  • Free tier extremely limited (0.5 vCPU, 1GB RAM, 4GB disk); suitable only for experiments
  • Standard and Premium pricing usage-based; specific costs not published; requires calculator or quote
  • Requires understanding of embeddings and vector search concepts; not suitable for SQL-only teams
  • Early-stage serverless offering (coming soon) suggests maturity gaps in that deployment model

Pricing, plan by plan

etcd

On request

No published plan breakdown. See the etcd review.

Qdrant

Free
  • FreeFree
    • Single-node cluster
    • 0.5 vCPU
    • 1GB RAM
  • StandardOn request
    • Dedicated resources
    • Flexible scaling
    • High availability
  • PremiumOn request
    • SSO and SAML
    • Private VPC links
    • 99.9% uptime SLA

Which should you pick?

Choose etcd if

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

Choose Qdrant if

  • You want to start without paying.
  • You work on Web, Self-hosted, Browser extension, Serverless (coming).
Qdrant review

Questions people ask

Is etcd or Qdrant better?
Neither clearly leads. etcd starts at On request and Qdrant at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, etcd or Qdrant?
Qdrant has a free tier; the other does not. Paid plans start at On request for etcd and Free for Qdrant.
Does etcd or Qdrant run on more platforms?
etcd runs on Web. Qdrant runs on Web, Self-hosted, Browser extension, Serverless (coming).
Can I use Qdrant for free?
Yes. Qdrant 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 Qdrant is typically brought in for.
What can etcd do that Qdrant 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.

Qdrant: Can I use Qdrant for free?

Yes, Qdrant offers a free tier that provides a single node cluster with 0.5 vCPU, 1GB RAM, and 4GB disk space. It includes free cloud inference with selected models and is described as free forever for testing and prototypes.

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.

Qdrant: How is Qdrant Cloud billing calculated?

Billing is calculated based on actual resource usage during each billing period. You are charged hourly for compute (vCPU), memory (GB), storage (GB), backups, and any paid inference tokens used.

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.

Qdrant: What happens if I scale beyond the free tier?

The Standard Tier uses the same usage-based billing model as the free tier but adds features like dedicated resources with flexible scaling, highly available setups with backup and disaster recovery, and a 99.5% uptime SLA.

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.

Qdrant: What SLA does Qdrant offer?

The Standard Tier provides 99.5% uptime SLA. The Premium Tier, which requires a minimum spend for enterprises, offers 99.9% uptime SLA along with single sign-on and private VPC links.

Source
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.

Qdrant: Are there dedicated cloud infrastructure options?

Yes, Qdrant offers Hybrid Cloud (runs on your infrastructure) and Private Cloud (complete isolation) options, both with custom pricing that requires contacting the sales team.

Source
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