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Keploy as a ScyllaDB testing framework

Keploy records the CQL binary protocol exchanges your service has with ScyllaDB, then replays them byte for byte in tests. Your Cassandra driver runs unchanged and does its real work on every run, but CI needs no ScyllaDB instance, no schema and no seed data.

Generate ScyllaDB tests free
keploy record -c "<your app start command>"
18.5K+VS Code1.2M+300M+mocks created

What Keploy gives a ScyllaDB team

Every ScyllaDB call your service makes

Keploy records CQL query results at the binary protocol Scylla speaks, so a service that reads from Scylla can be tested with no cluster and no keyspace in CI.

  • CQL binary protocol captured
  • Prepared statements captured
  • Real column types
  • No cluster in CI
The problem

Why ScyllaDB 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.

Three ways to do it

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

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

Select any row for the full comparison, with code.

Same coverage, three costs

What you write for ScyllaDB 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 ScyllaDB 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 ScyllaDB 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 ScyllaDB per suite. Needs a Docker daemon
# available wherever the tests run, including CI.
with DockerContainer("scylladb: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 ScyllaDB. 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: CQL
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.

Keploy vs the alternatives

ScyllaDB 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.

Best in classStrongPartialNot covered

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

How it works

Record your ScyllaDB app once, replay it forever

Keploy sits below your ScyllaDB 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.

Keploy records a GET call to /api/v1/orders/{id} on a ScyllaDB service and captures the dependency calls it makes.

ScyllaDB logo
Your ScyllaDB app
GET/api/v1/orders/{id}200
RecordingKeploy proxyeBPF · userspace
.NET logo
.NETCassandraCSharpDriver
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.
Mock coverage

What Keploy mocks for ScyllaDB, with zero config

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

Quick start

Your first ScyllaDB test suite in under five minutes

Every command below runs against your existing ScyllaDB 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 ScyllaDB 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

Ready to try it on your own ScyllaDB service?

Ecosystem

Works with the rest of your ScyllaDB stack

Keploy records at the network layer, so framework and driver choices inside your ScyllaDB app do not change how it captures traffic.

FAQ

ScyllaDB testing with Keploy: common questions

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