Do I need CouchDB running to replay?

No. The recorded responses are served from the test set, so a replay run needs no CouchDB instance at all. You need it once, during the recording pass.

Is my HTTP client still exercised?

Yes. Keploy replays at the protocol, so the client parses, converts and decodes exactly as it does in production. That is the difference from a stubbed client, which skips all of it.

How do I refresh the recordings?

Record again. One command re-captures every CouchDB interaction, so a schema or response change surfaces as a diff instead of a stale fixture that still passes.

What about _rev conflicts?

Revision ids change on every write, so Keploy detects them as non-deterministic and excludes them from comparison while still asserting the rest of the document.

Does Keploy replace Testcontainers?

Not where you need the real engine, and that is worth being clear about. Use Testcontainers when a test genuinely has to exercise CouchDB itself. Keploy covers the much larger set of tests that only need the responses.

Keploy as a CouchDB testing framework

Keploy records the HTTP and JSON API exchanges your service has with CouchDB, then replays them byte for byte in tests. Your HTTP client runs unchanged and does its real work on every run, but CI needs no CouchDB instance, no schema and no seed data.

Generate CouchDB tests free

keploy record -c "<your app start command>"

18.5K+

1.2M+300M+mocks createdSlack

What Keploy gives a CouchDB team

Every CouchDB call your service makes

Keploy records CouchDB's HTTP API exchanges, so a service that reads and writes documents can be tested with no CouchDB instance and no design documents to install.

HTTP API captured
View and Mango query results
Revision handling captured
No CouchDB in CI

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The problem

Why CouchDB integration tests slow teams down

The friction is rarely the assertions. It is everything around them — spinning up dependencies, keeping mocks honest, and repairing tests after every refactor.

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Three ways to do it

Testing CouchDB: by hand, with Testcontainers, or with Keploy

Testcontainers gives a test a real CouchDB at the cost of running one. A stubbed client is cheap but skips the driver. Keploy replays the real protocol with nothing running.

By hand

Testcontainers

With Keploy

Select any row for the full comparison, with code.

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Same coverage, three costs

What you write for CouchDB vs what Keploy records

All three produce the same assertion. Only the third still passes after the next refactor without anyone editing it.

By hand2–4 hours

order_repository_test.py

hand-written

from unittest.mock import MagicMock

# A stub CouchDB client: every reply is typed out here.

def test_reads_an_order():

client = MagicMock()

client.fetch.return_value = {

"id": "o-1",

"total": 4200,

"status": "NEW",

}

order = OrderRepository(client).find("o-1")

assert order.total == 4200

# Nothing here exercised the driver, so a type or encoding

# change in the real reply cannot fail this test.

A hand-written stub of the CouchDB client. The driver never runs.

Testcontainers1–2 hours

order_repository_container_test.py

tool-assisted

import pytest

from testcontainers.core.container import DockerContainer

@pytest.fixture(scope="session")

def client():

# Boots a real CouchDB per suite. Needs a Docker daemon

# available wherever the tests run, including CI.

with DockerContainer("couchdb:latest") as c:

c.start()

yield connect(c.get_container_host_ip(), c.get_exposed_port(0))

def test_reads_an_order(client):

# Schema and seed data are still written by hand.

seed(client, id="o-1", total=4200, status="NEW")

order = OrderRepository(client).find("o-1")

assert order.total == 4200

Testcontainers runs the real CouchDB. Fidelity is genuine; the job pays for it.

With Keploy~5 minutes

keploy/test-set-0/test-1.yaml

auto-generated

version: api.keploy.io/v1beta1

kind: Http

name: test-1

spec:

req:

method: POST

url: /orders/o-1/confirm

resp:

status_code: 200

body: '{"id":"o-1","status":"CONFIRMED","total":4200}'

assertions:

noise:

- body.confirmedAt

---

kind: Http

spec:

collection: orders

filter: { _id: "o-1" }

documents:

- { _id: "o-1", total: 4200, status: "NEW" }

---

kind: Http

spec:

request:

url: https://api.payments.example.com/v1/payment_intents/tok_123/confirm

response:

body: '{"status":"AUTHORIZED"}'

Recorded from one real request. Nothing here was typed by hand.

Times are estimates for authoring one endpoint’s coverage from scratch, not measurements.

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Keploy vs the alternatives

CouchDB testing tools, compared

The options a team on document and wide-column stores actually reaches for, and where each one genuinely wins. Select a row for the full comparison.

Keploy

Testcontainers

mongodb-memory-server

mongomock

Fongo

Postman

SmartBear ReadyAPI

Best in classStrongPartialNot covered

Assessments reflect each tool’s documented behaviour, not benchmark measurements.

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How it works

Record your CouchDB app once, replay it forever

Keploy sits below your CouchDB process at the network layer. It watches the calls your app already makes, then serves them back on replay so tests run with no dependencies attached.

Your CouchDB appGET/api/v1/orders/{id}200

RecordingKeploy proxyeBPF · userspace

JavaEktorp and the Cloudant client

PythonCouchdb and ibmcloudant

Node.jsNano

GoKivik

.NETMyCouch

An example shape of a captured call. Your own endpoints and dependencies come from your real traffic, so nothing here has to be written by hand.

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Mock coverage

What Keploy mocks for CouchDB, with zero config

5 of the 5 dependencies a typical CouchDB service talks to are stubbed from the recording itself — no mock classes, no fixture files, no containers in CI.

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Quick start

Your first CouchDB test suite in under five minutes

Every command below runs against your existing CouchDB service. Nothing in your source tree changes.

1
1Install the Keploy CLI
A single binary. It needs a Linux kernel with eBPF support, or Docker on macOS and Windows — and it adds nothing to your project's dependencies.
curl -sSL https://keploy.io/install.sh | bash
2
2Record your service
Pass the command you already use to start the app. Keploy runs it and watches every socket it opens.
keploy record -c "<your app start command>"
3
3Exercise the paths you care about
Use curl, your frontend, or an existing smoke script. Every request becomes a test case with its CouchDB calls captured alongside it.
curl -X POST localhost:8080/orders/o-1/confirm
curl localhost:8080/orders/o-1
4
4Replay in CI
Replay serves the recorded dependency responses, so the job needs no service containers and no Docker daemon.
keploy test -c "<your app start command>" --delay 10