Moving Data from SQLite to PostgreSQL: 3 Easy Methods

Many businesses rely on relational databases to manage transactional data. While SQLite offers a serverless, high-speed option, it lacks the robust capabilities needed for real-world applications like web development. PostgreSQL provides concurrent processing and other advanced features.

This article will guide you through two simple methods to migrate your SQLite data into a PostgreSQL database.

By moving from SQLite to PostgreSQL, you can optimize performance and unlock more powerful data management and querying for your applications. Let’s get started connecting these databases!

3 Methods for Connecting SQLite to PostgreSQL

Method 1: Using Hevo

Step 1. Set Up SQLite as the Source

• Go to your Hevo dashboard.
• Click “+ Create Pipeline”.
• Select SQLite as the source.
• Upload the SQLite .db file, or provide the file path if hosted.
• Configure the connection:
  • Name the pipeline.
  • Define tables to sync (or choose all).
  • Schedule sync frequency (real-time or batch).

Step 2. Configure PostgreSQL as the Destination

• In the same pipeline, click “Add Destination”.
• Choose PostgreSQL.
• Provide connection details:
  • Host (e.g., db.example.com)
  • Port (default: 5432)
  • Database name
  • Username & password
• Test the connection and save.

Step 3. Set Up Data Mapping & Transformation (Optional)

• Hevo auto-maps schema from SQLite to PostgreSQL.
• You can apply transformations using Python scripts or Hevo’s UI (optional).
• Enable data type casting to ensure compatibility (e.g., SQLite’s flexible typing vs PostgreSQL’s strict typing).

Step 4. Monitor Pipeline & Start Sync

Hevo logs all sync jobs, errors, and schema changes.

Click “Start Pipeline”.

Monitor data flow in the dashboard.

Method 2: SQLite to PostgreSQL using Django

Step 1: Create SQLite DB Dump Data Backup

python manage.py dumpdata > whole.json

You can also use the modified version of the above command by including natural primary & foreign keys as follows:

python manage.py dumpdata — natural-foreign — natural-primary > whole.json

It will generate the SQLite dump data in the JSON fixture format. It is suggested that you use this alternate command only if you face any error in restoring (loaddata) data to PostgreSQL.

Step 2: Generate a Postgres DB and User

Now, you have to install Postgres in your system’s operating system. Once that is in place, use the below command to log into it:

sudo su — postgres

psql

Next, generate a PostgreSQL database and create a new user. Provide the user with a password and grant it the required database permission:

create user john;create database nw_db;alter role hero with password ‘new_db@123’;grant all privileges on database new_db to john;alter database new_db owner to john;

Now, to connect SQLite to PostgreSQL, you need to configure the Settings.py tool.

Pro Tip: Connect any data source to PostgreSQL and watch your data load in real-time. Experience a hassle-free, zero-maintenance data load with Hevo.

Step 3: Configure Settings.py

In your system, write the following commands:

# install this package 
pip install psycopg2
settings.py
DATABASES = {
‘default’: {
‘ENGINE’: ‘django.db.backends.postgresql_psycopg2’,
‘NAME’: ‘new_db’,
‘USER’ : ‘john’,
‘PASSWORD’ : ‘new_db@123’,
‘HOST’ : ‘localhost’,
‘PORT’ : ‘5452’,
}
}

Next, delete all migration files and create a new migration file for each application. The following command will allow you to delete the old migration files:

find . -path “*/migrations/*.py” -not -name “__init__.py” -delete
find . -path “*/migrations/*.pyc” -delete
do
python manage.py makemigrations
python manage.py migrate

Also, delete the content types (mandatory steps) to avoid numerous errors as follows:

python manage.py shell
from django.contrib.contenttypes.models import ContentType
ContentType.objects.all().delete()

This step completes the task of developing an empty Postgres database. Now, you have to load data into the PostgreSQL database from fixtures.

Step 4: Import Required Fixture via Loaddata from SQLite to PostgreSQL

The final main step to connect SQLite to PostgreSQL requires you to disable every signal present in projects. This will safeguard you from getting unique prebuilt constraints. Finally, use the following command and load data to PostgreSQL database from fixtures:

python manage.py loaddata fixture/whole.json

With this step, you have moved data successfully from SQLite to PostgreSQL via fixtures.

Our comprehensive guide to PostgreSQL analytics can be a great resource if you’re keen on working with PostgreSQL.

Method 3: SQLite to PostgreSQL using pgloader

You can also use command instructs in pgloader to move data from a SQLite file. It supports automatic discovery of the schema, including building the indexes

Using default settings

Here is the simplest command line example, which might be all you need:

$pgloadersqlite:///path/to/file.dbpgsql://pguser@pghost/dbname

Using advanced options and a load command file

The command then would be:

$ pgloader db.load

Here’s an example of the db.load contents then:

load database

from sqlite:///Users/dim/Downloads/lastfm_tags.db

into postgresql:///tags

with include drop, create tables, create indexes, reset sequences

set work_mem to '16MB', maintenance_work_mem to '512 MB';

Explore more about: MySQL to PostgreSQL.

Best Practices to Migrate from SQLite to Postgres

Since you now know the steps required to connect SQLite to PostgreSQL, keep in mind the following practices while implementing the above method:

Handle Groups and Permissions:

In case you wish to use groups and permissions for moving data from SQLite to PostgreSQL, create a data dump without excluding the types (content) & permissions. This way, you can avoid errors while using the loaddata command, as groups heavily rely on permissions.

Migrate Early in the Project:

Always use SQLite for development only and perform the SQLite to PostgreSQL data transfer in the early stages of your projects. This is because the above-mentioned fixture method to connect SQLite to PostgreSQL operates on massive RAM for loading data. This means, if your SQLite holds more than 100MB of data, the method may falter.

Adjust Char Field Sizes:

You might have to change the char field of your model to max_length size. This is to ensure that you are not stumped by the error caused by the dumpdata command, which sometimes creates space in the charfield value. This way you will avoid errors like “in the model, field varying length 30 exceeds 30” while usingthe loaddata command to connect SQLite to PostgreSQL.

Conclusion

Migrating from SQLite to PostgreSQL unlocks advanced features like stronger SQL compliance, concurrency control, and efficient indexing, making it ideal for production-ready applications. Depending on your use case, you can choose Hevo for a quick no-code setup, Django fixtures for smaller projects, or pgloader for complex configurations. For instance, besides migrating data from SQLite, businesses also migrate their data from MySQL to PostgreSQL. Building an in-house solution for this process could be an expensive and time-consuming task.

While each method has its strengths, using a platform like Hevo ensures automation, real-time sync, and fewer chances of errors compared to manual approaches. With the right practices and tools, you can seamlessly move beyond SQLite’s limitations and harness PostgreSQL’s full potential for scalable, reliable applications.

Hevo Data is a No-code Data Pipeline solution that can help you import data from a vast sea of sources like MongoDB to your desired destination such as PostgreSQL, Data Warehouses, or BI tools.

Try Hevo and see the magic for yourself. Sign up for a free 14-day trial to streamline your data integration process. You may examine Hevo’s pricing plans and decide on the best plan for your business needs.

FAQ on SQLite to PostgreSQL