The Prisma P2023 error indicates a data type mismatch between your database and what Prisma expects based on your schema. This typically occurs due to integer overflow, invalid data types, failed conversions, or schema mismatches. The fix usually involves validating data types, migrating column types, or ensuring your schema matches your actual database structure.
The P2023 error in Prisma indicates "Inconsistent column data" - a critical runtime error that occurs when Prisma cannot safely convert a value retrieved from the database to the expected JavaScript type. This error is thrown when: - A database value cannot be converted to the type specified in your Prisma schema - Data in your database does not match the expected type definition - A conversion fails due to invalid input or out-of-range values For example, if your schema defines a field as an Int but the database contains a value that exceeds the maximum 32-bit integer size, or if a String field contains data that cannot be parsed as the declared type, Prisma will throw P2023. The error message provides details about what conversion failed and often suggests the specific action needed to fix it.
Examine the full error message to understand what conversion failed:
import { Prisma } from '@prisma/client';
try {
const record = await prisma.user.findUnique({
where: { id: 'some-id' }
});
} catch (error) {
if (error instanceof Prisma.PrismaClientKnownRequestError) {
if (error.code === 'P2023') {
console.log('Full error message:', error.message);
// Example: "Inconsistent column data: Conversion failed: Value 9223372036854775807
// does not fit in an INT column, try migrating the 'int' column type to BIGINT."
}
}
}Common error message patterns:
- "Conversion failed: Value X does not fit in an INT column" → Integer overflow
- "Failed to convert 'X' to 'Y'" → Type mismatch
- "Could not convert from 'base64 encoded bytes'" → Bytes conversion issue
- "List field did not return an Array" → Array parsing problem
- "Error creating UUID, invalid length" → Invalid UUID format
If you encounter "does not fit in an INT column" errors, migrate the column to BIGINT:
Step 1: Update your Prisma schema
model User {
id String @id @default(cuid())
largeNum BigInt // Changed from Int to BigInt
name String
}Step 2: Create a migration
npx prisma migrate dev --name migrate_int_to_bigintStep 3: Update your TypeScript code to handle BigInt
// Note: BigInt in JavaScript uses the 'n' suffix
const user = await prisma.user.findUnique({
where: { id: 'user-1' }
});
// user.largeNum is now a BigInt
console.log(typeof user.largeNum); // 'bigint'
// Convert to string if needed
const numberAsString = user.largeNum.toString();
// JSON serialization requires custom handling
JSON.stringify(user, (key, value) =>
typeof value === 'bigint' ? value.toString() : value
);Step 4: Handle BigInt in API responses
// Add a middleware or custom JSON replacer for API responses
const jsonReplacer = (key: string, value: any) => {
if (typeof value === 'bigint') {
return value.toString();
}
return value;
};
app.post('/api/users', async (req, res) => {
const user = await prisma.user.findUnique({
where: { id: 'user-1' }
});
res.json(JSON.parse(JSON.stringify(user, jsonReplacer)));
});Ensure your Prisma schema accurately reflects your actual database structure:
Step 1: Pull the actual database schema
npx prisma db pullThis introspects your database and updates schema.prisma to match reality.
Step 2: Compare your schema with the database
# View what changed
git diff prisma/schema.prismaStep 3: Fix discrepancies
If your intended schema is different from the database, create a migration:
// If database has VARCHAR but schema expects Int
model Product {
id String @id @default(cuid())
price Decimal @db.Decimal(10, 2) // Explicitly specify database type
quantity Int // Should match database type
}Step 4: Apply the migration
npx prisma migrate dev --name fix_schema_mismatchIf using MongoDB with Prisma, ensure numeric values are stored with the correct type:
Option 1: Fix data in MongoDB first
// MongoDB migration script
db.users.updateMany(
{ age: { $type: "string" } },
[
{
$set: {
age: { $toInt: "$age" }
}
}
]
);Option 2: Handle conversion during queries
// Prisma with explicit type casting
const users = await prisma.user.findMany({
select: {
id: true,
age: true
}
});
// Cast strings to numbers if needed
const usersWithCorrectTypes = users.map(user => ({
...user,
age: typeof user.age === 'string' ? parseInt(user.age, 10) : user.age
}));Option 3: Use Prisma migrations to transform data
-- SQL migration for MongoDB (if using MongoDB with SQL migration tool)
UPDATE users SET age = CAST(age AS INTEGER) WHERE age IS NOT NULL;If receiving "Error creating UUID, invalid length" errors:
import { validate as validateUUID } from 'uuid';
async function safeQuery(userId: string) {
// Validate UUID format before querying
if (!validateUUID(userId)) {
throw new Error(`Invalid UUID format: ${userId}`);
}
try {
return await prisma.user.findUnique({
where: { id: userId }
});
} catch (error) {
if (error instanceof Prisma.PrismaClientKnownRequestError &&
error.code === 'P2023') {
throw new Error('Invalid UUID in database or query');
}
throw error;
}
}
// In your API handlers
app.get('/users/:id', async (req, res) => {
try {
const user = await safeQuery(req.params.id);
res.json(user);
} catch (error) {
res.status(400).json({ error: error.message });
}
});If P2023 errors started appearing after enabling preview features, disable them:
Check your schema.prisma for preview features:
// Remove or comment out problematic features
generator client {
provider = "prisma-client-js"
// previewFeatures = ["relationJoins"] // Comment out
}Known problematic combinations:
- relationJoins with Bytes fields (Prisma 5.10.2+)
- PostgreSQL adapter with String[] @db.Citext
Regenerate Prisma Client:
npx prisma generateCheck if the P2023 error persists. If removing a preview feature fixes it, report the issue to Prisma GitHub.
Implement error handling for P2023 to prevent application crashes:
import { Prisma } from '@prisma/client';
async function fetchUserWithErrorHandling(userId: string) {
try {
return await prisma.user.findUnique({
where: { id: userId }
});
} catch (error) {
if (error instanceof Prisma.PrismaClientKnownRequestError) {
if (error.code === 'P2023') {
console.error('Data consistency error:', error.message);
// Log for debugging
logger.error('P2023 inconsistent column data', {
userId,
originalError: error.meta
});
// Return graceful error to user
throw new Error(
'Unable to retrieve user data. Please contact support if this persists.'
);
}
}
throw error;
}
}
// In Express/Next.js
app.get('/api/users/:id', async (req, res) => {
try {
const user = await fetchUserWithErrorHandling(req.params.id);
res.json(user);
} catch (error) {
res.status(500).json({
error: error.message,
code: 'INTERNAL_ERROR'
});
}
});Version-Specific Behavior:
- Prisma 4.0.0+: Stricter type checking on integer values (may trigger new P2023 errors on existing data)
- Prisma 5.10.2+: relationJoins preview feature has known Bytes conversion bugs
- Prisma 6.0+: PostgreSQL adapter has issues with citext array fields
Database-Specific Issues:
SQLite: Integer overflow checks are strict. Values exceeding 32-bit integer limits require BigInt type.
PostgreSQL:
- Citext arrays may fail to parse with certain adapter versions
- Timestamptz fields can cause conversion failures
- Use explicit @db types: @db.Timestamp, @db.Timestamptz
MySQL: Type mismatches are common with JSON fields. Always validate JSON before storing.
MongoDB: String-to-number conversion is a frequent source of P2023. Ensure documents use correct BSON types.
Recovery Strategies for Production:
1. Data Audit: Query the database directly to identify problematic rows
-- PostgreSQL example
SELECT * FROM "User" WHERE id = 'affected-id';2. Partial Migrations: If only specific rows are affected, update them in isolation
// Fetch without the problematic field first
const user = await prisma.user.findUnique({
where: { id: 'user-1' },
select: { id: true, name: true } // Skip problematic field
});3. Rollback and Investigate: If errors appeared after schema changes
npx prisma migrate resolve --rolled-back "migration-name"Common Misconceptions:
- P2023 is NOT a connection issue (it's data integrity)
- P2023 is NOT solved by reconnecting (the data mismatch persists)
- P2023 requires fixing the actual data or schema, not just error handling
Testing P2023 Scenarios:
describe('P2023 Error Handling', () => {
it('should handle inconsistent column data gracefully', async () => {
// Manually insert invalid data (bypass Prisma validation)
await prisma.$executeRawUnsafe(
'INSERT INTO "User" (id, age) VALUES ($1, $2)',
['test-id', '99999999999999999999'] // Value too large for Int
);
// Attempt to read should throw P2023
await expect(
prisma.user.findUnique({ where: { id: 'test-id' } })
).rejects.toThrow('P2023');
});
});P1013: The provided database string is invalid
The provided database string is invalid
P1000: Authentication failed against database server
Authentication failed against database server
P1010: User was denied access on the database
How to fix "P1010: User was denied access on the database" in Prisma
P5008: Usage exceeded, upgrade your plan (Accelerate)
How to fix "Usage exceeded, upgrade your plan" in Prisma Accelerate
P3021: Foreign keys cannot be created on this database
How to fix 'P3021: Foreign keys cannot be created on this database' in Prisma