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Migrate from Turso to Lakebase Postgres

Summary: Migration guide for moving a Turso (libSQL/SQLite) database to Lakebase Postgres using pgloader. Dumps the Turso database to a local SQLite file with the Turso CLI, then loads it into Neon where pgloader converts SQLite type affinities to Postgres types. Use this guide when the source is Turso or SQLite; it also covers swapping Turso drivers for the Neon serverless driver, translating ? placeholders to $1 parameters, adapting dialect differences like LIKE vs ILIKE, and verifying sequences after migration. Neon's Free plan supports up to 0.5 GB; larger Turso databases require a paid Neon plan.

This guide describes how to migrate your Turso database to Lakebase Postgres using pgloader.

pgloader is an open-source data loading and migration tool that efficiently transfers data from various sources (like CSV, MySQL, SQLite, MS SQL, etc.) into Postgres, handling schema and data transformations on the fly. Since Turso databases are SQLite-compatible, you can dump them to a local SQLite file and then use pgloader to migrate that file to Lakebase Postgres.

Before you begin, ensure you have the following:

  • A Neon account and a project. If you don't have one, see Sign up.
  • A database created in your Neon project. For instructions, see Create a database.
  • The Turso CLI installed. You'll use it to export your database.
  • The sqlite3 command-line tool, typically pre-installed on macOS and Linux.
  • Neon's Free plan supports 0.5 GB of data. If your data size is more than 0.5 GB, you'll need to upgrade to one of Neon's paid plans. See Neon plans for more information.

A review of the pgloader SQLite to Postgres Guide is also recommended. It provides a comprehensive overview of pgloader's capabilities and type mappings, which will be helpful for understanding the migration process.

Understanding SQLite and Postgres data types

Section titled “Understanding SQLite and Postgres data types”

Before migrating from Turso to Postgres, it's helpful to understand a key difference in how they handle data types. Turso, built on SQLite, uses a flexible typing system called "type affinity". You can store any type of data in any column, regardless of its declared type. Postgres uses a strict, static typing system. Data inserted into a column must precisely match the column's declared data type.

When converting a database, SQLite's type affinities are mapped to appropriate Postgres types. Here is a summary of the common mappings:

Data Type Category SQLite PostgreSQL Key Differences & Notes
Integer INTEGER SMALLINT (2 bytes)
INTEGER (4 bytes)
BIGINT (8 bytes)
SQLite's INTEGER is a flexible-size signed integer, storing values in 1, 2, 3, 4, 6, or 8 bytes depending on the magnitude of the value. PostgreSQL offers fixed-size integers for more granular control over storage and performance.
Auto-incrementing Integer INTEGER PRIMARY KEY SMALLSERIAL (2 bytes)
SERIAL (4 bytes)
BIGSERIAL (8 bytes)
In SQLite, declaring a column as INTEGER PRIMARY KEY automatically makes it an alias for the rowid and thus auto-incrementing. PostgreSQL provides the SERIAL pseudo-types, which create a sequence object to generate unique identifiers.
Floating-Point REAL REAL (4 bytes)
DOUBLE PRECISION (8 bytes)
SQLite's REAL is an 8-byte IEEE floating-point number. PostgreSQL offers both single-precision (REAL) and double-precision (DOUBLE PRECISION) floating-point numbers.
Arbitrary Precision Numeric NUMERIC NUMERIC(precision, scale)
DECIMAL(precision, scale)
SQLite's NUMERIC affinity will attempt to store data as INTEGER or REAL, or as TEXT if it cannot be losslessly converted. PostgreSQL's NUMERIC and DECIMAL types are for exact decimal arithmetic, crucial for financial and scientific applications, allowing for user-defined precision and scale.
String TEXT
VARCHAR(n)
CHAR(n)
TEXT
VARCHAR(n)
CHAR(n)
While both databases accept these type names, in SQLite, they all have a TEXT affinity. The length (n) is not enforced in SQLite. In PostgreSQL, VARCHAR(n) enforces a maximum length, and CHAR(n) is a fixed-length, blank-padded string. TEXT in PostgreSQL has no predefined length limit.
Binary Data BLOB BYTEA Both are used for storing raw binary data.
Date & Time TEXT
REAL
INTEGER
DATE
TIME
TIMESTAMP
TIMESTAMPTZ (with time zone)
INTERVAL
SQLite has no dedicated date/time storage class; they are typically stored as TEXT (ISO-8601 strings), REAL (Julian day numbers), or INTEGER (Unix timestamps). PostgreSQL provides a rich set of specific date and time types with built-in functions for complex date and time arithmetic and time zone handling.
Boolean INTEGER (0 for false, 1 for true) BOOLEAN SQLite does not have a native boolean type and commonly uses INTEGER with values 0 and 1. PostgreSQL has a dedicated BOOLEAN type that stores true or false.
JSON TEXT JSON
JSONB
In SQLite, JSON data is stored as TEXT. PostgreSQL offers two dedicated JSON types: JSON for storing the raw JSON text and JSONB for a decomposed binary format that is more efficient for indexing and querying.
Unique Identifier - UUID PostgreSQL has a dedicated UUID data type for storing Universally Unique Identifiers, which is not present in SQLite.
Array - data_type[] PostgreSQL supports arrays of any built-in or user-defined data type, a powerful feature for storing lists of values in a single column. SQLite does not have a native array type.

If you haven't authenticated the Turso CLI yet, run:

Shell
turso auth login

Follow the prompts to log in with your Turso account credentials. This will allow you to access your Turso databases and export them for migration.

Dump your Turso database to a local sql file using the turso db shell command with the .dump option:

Bash
turso db shell <database-name> .dump > dump.sql

Replace <database-name> with the name of your Turso database. This command connects to your Turso database and runs the .dump command, which outputs the full schema and data as SQL statements.

Next, generate a local SQLite database file from the dump:

Bash
sqlite3 turso_export.db < dump.sql

You now have a turso_export.db file containing your data, ready for migration.

Retrieve your Neon database connection string

Section titled “Retrieve your Neon database connection string”

Log in to the Neon Console. Find the connection string for your database by clicking the Connect button in the Console nav. Make sure the Connection pooling toggle is disabled:

Connection details modal with connection pooling disabled

Your connection string should look similar to this:

Bash
postgresql://alex:AbC123dEf@ep-cool-darkness-123456.us-east-2.aws.neon.tech/dbname?sslmode=require

Important: You will need to remove &channel_binding=require from the connection string, as pgloader does not support channel binding and throws an error when it is present.

Now, modify this connection string to pass your endpoint ID (ep-cool-darkness-123456 in this example) to Neon with your password using the endpoint keyword, as shown here:

Bash
postgresql://alex:endpoint=ep-cool-darkness-123456;AbC123dEf@ep-cool-darkness-123456.us-east-2.aws.neon.tech/dbname?sslmode=require

Note: Passing the endpoint ID with your password is a required workaround for some Postgres drivers, including the one used by pgloader. For more information, see Connect with an endpoint ID.

Keep your modified Neon connection string handy.

Install the pgloader utility using your preferred method:

  • For macOS with Homebrew: brew install pgloader
  • For Debian/Ubuntu: sudo apt-get install pgloader
  • For Docker: Pull the latest image with docker pull dimitri/pgloader:latest

For other systems, see Installing pgloader.

For a straightforward migration, run pgloader directly from the command line:

Shell
pgloader sqlite://turso_export.db "postgresql://alex:endpoint=ep-cool-darkness-123456;AbC123dEf@ep-cool-darkness-123456.us-east-2.aws.neon.tech/dbname?sslmode=require"

Make sure to enclose the Postgres connection string in quotes to prevent shell interpretation issues.

The command output will look similar to this:

Bash
2025-06-27T08:26:19.941000Z LOG report summary reset
             table name     errors       rows      bytes      total time
-----------------------  ---------  ---------  ---------  --------------
                  fetch          0          0                     0.000s
        fetch meta data          0          5                     0.204s
         Create Schemas          0          0                     0.108s
       Create SQL Types          0          0                     0.222s
          Create tables          0          4                     1.307s
         Set Table OIDs          0          2                     0.121s
-----------------------  ---------  ---------  ---------  --------------
                authors          0          3     0.1 kB          1.082s
                  books          0          5     0.2 kB          0.993s
-----------------------  ---------  ---------  ---------  --------------
COPY Threads Completion          0          4                     1.080s
 Index Build Completion          0          2                     2.342s
         Create Indexes          0          2                     0.662s
        Reset Sequences          0          0                     1.297s
           Primary Keys          0          2                     0.650s
    Create Foreign Keys          0          1                     0.339s
        Create Triggers          0          0                     0.211s
       Install Comments          0          0                     0.000s
-----------------------  ---------  ---------  ---------  --------------
      Total import time          ✓          8     0.3 kB          6.581s

pgloader will automatically create the necessary tables and indexes in your Lakebase Postgres database, and transfer all data from the turso_export.db file. The summary report at the end confirms that the migration completed successfully without errors.

For better control over the destination schema, create a pgloader load file. This lets you cast columns to specific Postgres types.

For example, if you have an authors table with an id column that is an INTEGER PRIMARY KEY in Turso (SQLite), you can cast it to SERIAL in Postgres. Similarly, if you have a published_date column stored as TEXT, you can cast it to DATE

Create a file named turso.load with the following content, replacing the connection strings as needed:

SQL
LOAD DATABASE
    FROM sqlite://turso_export.db
    INTO postgresql://alex:endpoint=ep-cool-darkness-123456;AbC123dEf@ep-cool-darkness-123456.us-east-2.aws.neon.tech/dbname?sslmode=require

WITH
    include drop,
    create tables,
    create indexes,
    reset sequences,
    downcase identifiers

CAST
    -- Cast integer primary keys to SERIAL
    column authors.id to serial,
    column books.id to serial,

    -- Cast text date columns to Postgres DATE
    column books.published_date to date;

Run the migration using the load file:

Shell
pgloader turso.load

The migration will produce a cleaner Postgres schema with SERIAL primary keys and proper Postgres date types.

After migrating, always verify your data.

The reset sequences option in the load file ensures that auto-incrementing columns start from the correct value. Connect to your Neon database using psql or the Neon SQL Editor and check the next value for a table's sequence:

SQL
SELECT nextval(pg_get_serial_sequence('books', 'id'));

This should return a value one higher than the max id in the books table. If it doesn't, you can reset it manually:

SQL
SELECT setval(
    pg_get_serial_sequence('books', 'id'),
    (SELECT MAX(id) FROM books) + 1
);

Compare row counts between your Turso source and Neon destination:

SQL
SELECT count(*) FROM books;
SELECT count(*) FROM authors;

After migrating your database schema and data to Neon, you must update your application code to connect to Neon and execute queries using a Postgres driver instead of the Turso SQLite client.

First, replace your Turso database client (such as @tursodatabase/serverless or @libsql/client) with a Postgres-compatible driver. For serverless or edge environments, Neon's serverless driver is a great choice.

@tursodatabase/serverless

Bash
npm uninstall @tursodatabase/serverless
npm install @neondatabase/serverless # or npm install pg

@libsql/client

Bash
npm uninstall @libsql/client
npm install @neondatabase/serverless # or npm install pg

Next, update your environment variables with your Neon connection string retrieved from the Neon Console:

text
DATABASE_URL="postgresql://alex:AbC123dEf@ep-cool-darkness-123456.us-east-2.aws.neon.tech/dbname?sslmode=require"

Then, update your database connection initialization.

Before (Turso):

@tursodatabase/serverless

JavaScript
import { connect } from "@tursodatabase/serverless";

const db = connect({
  url: process.env.TURSO_DATABASE_URL,
  authToken: process.env.TURSO_AUTH_TOKEN,
});

@libsql/client

JavaScript
import { createClient } from "@libsql/client";

const db = createClient({...config});

After (Neon):

Neon serverless driver

JavaScript
import { neon } from '@neondatabase/serverless';
const sql = neon(process.env.DATABASE_URL);

node-postgres

JavaScript
import { Pool } from 'pg';
const pool = new Pool({
  connectionString: process.env.DATABASE_URL,
  ssl: true,
});

When converting your Turso queries to run against Postgres, you must adapt how statements are prepared and executed.

You need to transition from SQLite's parameter binding (often using ? placeholders) and driver-specific methods (.run(), .all(), .get()) to standard Postgres driver syntax. For example, with the Neon serverless driver, you can use tagged template literals for queries, while with node-postgres, you use parameterized queries with $1, $2, etc.

Before (Turso):

@tursodatabase/serverless

JavaScript
// Inserting data
const insertUser = db.prepare("INSERT INTO users (username) VALUES (?)");
await insertUser.run("alice");

// Querying data
const stmt = db.prepare("SELECT * FROM users");
const users = await stmt.all();

@libsql/client

JavaScript
// Inserting data
await db.execute({
    sql: "INSERT INTO users (username) VALUES (?)",
    args: ["alice"],
});

// Querying data
const rs = await db.execute("SELECT * FROM users");
const users = rs.rows;

After (Neon):

Neon serverless driver

JavaScript
// Inserting data
await sql`INSERT INTO users (username) VALUES (${'alice'})`;

// Querying data
const users = await sql`SELECT * FROM users`;

node-postgres

JavaScript
// Inserting data
await pool.query('INSERT INTO users (username) VALUES ($1)', ['alice']);

// Querying data
const { rows: users } = await pool.query('SELECT * FROM users');

Turso (SQLite) and Postgres use different SQL dialects. Here are the key differences you'll need to address when converting your application queries.

SQLite has no native boolean type -- it stores true/false as integers 1/0. Postgres has a dedicated BOOLEAN type with true/false values.

Before (Turso/SQLite):

SQL
SELECT * FROM users WHERE active = 1;
INSERT INTO users (username, active) VALUES ('alice', 1);

After (Neon/Postgres):

SQL
SELECT * FROM users WHERE active = true;
INSERT INTO users (username, active) VALUES ('alice', true);

SQLite's LIKE operator is case-insensitive for ASCII characters by default. Postgres's LIKE is case-sensitive; use ILIKE for case-insensitive matching, or LOWER() for comparisons.

Before (Turso/SQLite):

SQL
SELECT * FROM users WHERE username LIKE '%alice%';

After (Neon/Postgres):

SQL
SELECT * FROM users WHERE username ILIKE '%alice%';

Alternatively, normalize both sides:

SQL
SELECT * FROM users WHERE LOWER(username) LIKE LOWER('%alice%');

SQLite and Postgres use different built-in functions for date and time operations.

Before (Turso/SQLite):

SQL
-- Current timestamp
INSERT INTO logs (message, created_at) VALUES ('startup', datetime('now'));

-- Formatting a timestamp
SELECT strftime('%Y-%m-%d', created_at) FROM logs;

After (Neon/Postgres):

SQL
-- Current timestamp
INSERT INTO logs (message, created_at) VALUES ('startup', NOW());

-- Formatting a timestamp
SELECT to_char(created_at, 'YYYY-MM-DD') FROM logs;
Operation SQLite Postgres
Current timestamp datetime('now') NOW() or CURRENT_TIMESTAMP
Current date date('now') CURRENT_DATE
Format timestamp strftime(format, ts) to_char(ts, format)
Date arithmetic (add 7 days) datetime(ts, '+7 days') ts + INTERVAL '7 days'
Extract part of a date (year) strftime('%Y', ts) EXTRACT(YEAR FROM ts)

If you run pgloader from a Docker container and encounter an SSL verify error: 20 X509_V_ERR_UNABLE_TO_GET_ISSUER_CERT_LOCALLY, you may need to disable SSL certificate verification.

Modify your load file to set sslmode=allow in the Postgres connection string.

SQL
LOAD DATABASE
    FROM sqlite:///data/turso_export.db
    INTO postgresql://.../dbname?sslmode=allow;
...

Then, run the Docker command with the --no-ssl-cert-verification flag. Mount your database and load files into the container's /data directory.

Shell
docker run --rm -v /path/to/your/files:/data \
  dimitri/pgloader:latest \
  pgloader --no-ssl-cert-verification /data/turso.load


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