How do I test SQLite queries without a fixture database?

Record your application once with Keploy against your development database file. Each statement and the rows the engine returned are captured together, then replayed in tests — so no .sqlite file needs to be committed.

Should I use SQLite in tests if production runs Postgres?

It is a common shortcut and a real risk: SQLite's flexible typing, date handling, and feature set differ from Postgres. Recording against the real database with Keploy removes the tradeoff entirely.

Does Keploy capture SQLite transactions?

Yes. Statement order, savepoints, and commit boundaries are all part of what Keploy records, so a multi-statement transaction replays in the same order with the same results it originally received.

Does Keploy work with better-sqlite3 and rusqlite?

Yes. Capture happens at the driver boundary rather than inside the engine, so Go's database/sql, better-sqlite3, Python's sqlite3, rusqlite, and sqlx all record and replay the same statements.

Is Keploy free to use with SQLite?

Yes. The Keploy CLI is open source under Apache 2.0 and free to run on any service with no seat limits. Nothing is installed into SQLite and no extension is required.

Keploy as a SQLite testing framework

Keploy records the queries your app issues against SQLite together with the rows returned, then replays them during tests. CI needs no fixture database file, no schema rebuild, and no seed step — and the recorded rows come from a real SQLite engine.

Generate SQLite tests free

keploy record -c "./orders-service"

18.4K+

1.2M+300M+mocks createdSlack

What Keploy gives a SQLite team

Captured at the query boundary

SQLite is in-process rather than a server, so Keploy records at the driver boundary: the statement, its bound parameters, and the rows returned. What replays is what the real engine produced.

Statements captured with bound parameters
Real rows and column types
Transactions replay in order
Below the driver, above the file

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The problem

Why SQLite 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 SQLite: by hand, with in-memory SQLite, or with Keploy

An in-memory SQLite database is fast and needs its schema rebuilt every run. Keploy records the rows a request actually read, so replay needs neither a schema nor a file.

By hand

in-memory SQLite

With Keploy

Select any row for the full comparison, with code.

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Same coverage, three costs

What you write for SQLite 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_store_stub.go

hand-written

// Hand-written stub: no SQL is parsed or type-converted.

package store

type StubOrderStore struct {

rows map[string]Order

}

func NewStubOrderStore() *StubOrderStore {

return &StubOrderStore{rows: map[string]Order{

"ord_1": {ID: "ord_1", AmountMinor: 4200, State: "NEW"},

}}

}

func (s *StubOrderStore) Get(id string) (Order, error) {

return s.rows[id], nil

}

func (s *StubOrderStore) SetState(id, state string) error {

// No CHECK constraint or NOT NULL is enforced here.

o := s.rows[id]

o.State = state

s.rows[id] = o

return nil

}

Column affinity, constraints, and SQLite's flexible typing are all absent, so a type surprise reaches production unseen.

in-memory SQLite1–2 hours

order_store_test.go

tool-assisted

// In-memory SQLite: real engine, schema rebuilt per test.

package store

import (

"database/sql"

"testing"

_ "modernc.org/sqlite"

)

func TestReadsASeededOrder(t *testing.T) {

db, err := sql.Open("sqlite", ":memory:")

if err != nil {

t.Fatal(err)

}

defer db.Close()

// Rebuilt for every test in the package.

mustExec(t, db, schemaSQL)

mustExec(t, db, `INSERT INTO orders VALUES ('ord_1', 4200, 'NEW')`)

order, err := New(db).Get("ord_1")

if err != nil || order.AmountMinor != 4200 {

t.Fatalf("got %+v err %v", order, err)

}

Real SQLite semantics and no server — and the schema plus seed data are rebuilt in every test, and this is not the database production runs.

With Keploy~5 minutes

mocks.yaml

auto-generated

# Recorded with: keploy record -c './orders-service'

# The SQLite response, captured at the driver boundary.

version: api.keploy.io/v1beta1

kind: SQL

name: mock-2

spec:

request:

query: "SELECT id, amount_minor, state FROM orders WHERE id = ?"

params:

- "ord_1"

response:

columns:

- name: id

type: TEXT

- name: amount_minor

type: INTEGER

- name: state

type: TEXT

rows:

- id: "ord_1"

amount_minor: 4200

state: "NEW"

rows_affected: 0

No fixture file and no schema rebuild: the statement and the rows the engine returned are recorded together and replayed as a pair.

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

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Keploy vs the alternatives

SQLite testing tools, compared

The options a team on relational databases actually reaches for, and where each one genuinely wins. Select a row for the full comparison.

Keploy

Testcontainers

H2

DBUnit

pg-mem

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 SQLite app once, replay it forever

Keploy sits below your SQLite 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 SQLite appGET/api/v1/orders/{id}200

RecordingKeploy proxyeBPF · userspace

Godatabase/sql with mattn or modernc drivers

Node.jsbetter-sqlite3, node:sqlite, and Prisma

Pythonthe sqlite3 module and SQLAlchemy

Rustrusqlite and sqlx

+2 more SQLite clients

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

SQLite clients Keploy records, driver by driver

Keploy captures SQLite at the wire protocol, so 4 of these 6 clients need no adapter, no test double, and no SQLite instance in CI.

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Quick start

Your first SQLite test suite in under five minutes

Every command below runs against your existing SQLite 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 "./orders-service"
3
3Exercise the paths you care about
Run the app against your development database file. Every statement and the rows it returned are captured together.
curl localhost:8080/orders/ord_1
curl localhost:8080/orders/summary?state=NEW
4
4Replay in CI
Replay serves the recorded dependency responses, so the job needs no service containers and no Docker daemon.
keploy test -c "./orders-service" --delay 6