Get started with Typesense

In this quickstart, you’ll create a real-time data pipeline that streams changes from a Postgres database to a Typesense collection. You’ll:

Boot Sequin
Connect to a sample playground database
Create a Typesense collection
Set up a sink to sync changes to Typesense
See your changes flow in real-time

By the end, you’ll have hands-on experience setting up Postgres change data capture (CDC) with Sequin and Typesense.

This is the quickstart for streaming Postgres to Typesense. See the how-to guide for an explanation of how to use the Typesense sink or the reference for details on all configuration options.

Run Sequin

The easiest way to get started with Sequin is with our Docker Compose file. This file starts a Postgres database, Redis instance, and Sequin server.

Create directory and start services

Download sequin-docker-compose.zip.
Unzip the file.
Navigate to the unzipped directory and start the services:

cd sequin-docker-compose && docker compose up -d

Alternative: Download with curl

curl -L https://github.com/sequinstream/sequin/releases/latest/download/sequin-docker-compose.zip -o sequin-docker-compose.zip \
  && unzip sequin-docker-compose.zip && rm sequin-docker-compose.zip
cd sequin-docker-compose && docker compose up -d

Alternative: Clone the repository

git clone git@github.com:sequinstream/sequin.git
cd sequin/docker
docker compose up -d

Verify services are running

Check that Sequin is running using docker ps:

docker ps

You should see output like the following:

CONTAINER ID   IMAGE                           COMMAND                  CREATED          STATUS                    PORTS                              NAMES
bd5c458cabde   sequin/sequin:latest            "/scripts/start_comm…"   11 seconds ago   Up 9 seconds              4000/tcp, 0.0.0.0:7376->7376/tcp   sequin-sequin-1
3bacd89765e7   grafana/grafana                 "/run.sh"                11 seconds ago   Up 11 seconds             0.0.0.0:3000->3000/tcp             sequin-sequin_grafana-1
3ad41319a66c   postgres:16                     "docker-entrypoint.s…"   11 seconds ago   Up 11 seconds (healthy)   0.0.0.0:7377->5432/tcp             sequin-sequin_postgres-1
6139a5fc4e80   redis:7                         "docker-entrypoint.s…"   11 seconds ago   Up 11 seconds             0.0.0.0:7378->6379/tcp             sequin-sequin_redis-1
7e07a5b052de   prom/prometheus                 "/bin/prometheus --c…"   11 seconds ago   Up 11 seconds             0.0.0.0:9090->9090/tcp             sequin-sequin_prometheus-1

Sequin, Postgres, Redis, Prometheus, and Grafana should be up and running (status: Up).

Login

The Docker Compose file automatically configures Sequin with an admin user and a playground database.Let’s log in to the Sequin web console:

Open the web console

After starting the Docker Compose services, open the Sequin web console at http://localhost:7376:

Sequin login page, allowing login with default credentials

Use the following default credentials to login:

Email:

admin@sequinstream.com

Password:

sequinpassword!

View the playground database

To get you started quickly, Sequin’s Docker Compose file creates a logical database called sequin_playground with a sample dataset in the public.products table.Let’s take a look:

Navigate to Databases

In the Sequin web console, click Databases in the sidebar.

Select playground database

Click on the pre-configured sequin-playground database:

The database “Health” should be green.

View contents of the products table

Let’s get a sense of what’s in the products table. Run the following command:

docker exec -i sequin-sequin_postgres-1 \
  psql -U postgres -d sequin_playground -c \
  "select id, name, price from products;"

This command connects to the running Postgres container and runs a psql command.

You should see a list of the rows in the products table:

  id |         name          | price 
----+-----------------------+-------
  1 | Avocados (3 pack)     |  5.99
  2 | Flank Steak (1 lb)    |  8.99
  3 | Salmon Fillet (12 oz) | 14.99
  4 | Baby Spinach (16 oz)  |  4.99
  5 | Sourdough Bread       |  6.99
  6 | Blueberries (6 oz)    |  3.99
(6 rows)

We’ll make modifications to this table in a bit.

Create a Typesense Collection

First, let’s start Typesense and create a collection to store our product data:

Start Typesense

Typesense offers a docker image that can be run locally. Let’s start it up:

docker run -d \
  --name typesense-server \
  -p 8108:8108 \
  -v ./typesense-data:/data \
  --restart on-failure \
  typesense/typesense:29.0 \
  --data-dir /data \
  --api-key=my-api-key \
  --enable-cors

Create the collection

Run the following command to create a new collection called “products”:

curl -X POST http://localhost:8108/collections \
  -H "Content-Type: application/json" \
  -H "X-TYPESENSE-API-KEY: my-api-key" \
  -d '{
    "name": "products",
    "fields": [
      {"name": ".*", "type": "auto" }
    ]
  }'

This creates a collection that will automatically detect field types from our data.

Verify the collection

You can verify the collection was created by searching it:

curl -X GET "http://localhost:8108/collections/products/documents/search?q=*" \
  -H "X-TYPESENSE-API-KEY: my-api-key"

The collection should be empty initially.

{
  "found": 0,
  "hits": [],
  "out_of": 6,
  "page": 1
}

Create a Typesense Sink

With the playground database connected and Typesense collection created, you can create a sink. This sink will send changes to the products table to your Typesense collection:

Navigate to Sinks

Click “Sinks” in the sidebar navigation, then click “Create Sink”.

Select sink type

Select “Typesense” as the sink type and click “Continue”.

Note "Source" configuration

In the “Source” card, note that the sequin-playground database is selected and all schemas and tables are included. Leave these defaults:

Source card showing the sequin_playground database and products table

Setup a transform

In the Transform card, click the toggle to view existing transforms. None exist, so click ”+ Create new transform” which will open a window for creating a new transform.For “Transform name”, put products-typesense. For “Transform type”, select “Transform function”.In the “Transform function” field, input the following code:

def transform(action, record, changes, metadata) do
  record
  |> Map.take(["id", "name", "price"])
  # Typesense requires `id` to be a string
  |> Map.update("id", nil, fn id ->
    cond do
      is_binary(id) -> id
      is_integer(id) -> Integer.to_string(id)
      true -> to_string(id)
    end
  end)
end

This transform will take the id, name, and price fields from the products table and use them to create a new document in Typesense.

Click “Create Transform”.You can close the transform tab and navigate back to the Typesense sink create page.Now, select the products-typesense transform in the “Transform” list. (If you don’t see it, click the refresh icon.)

Setup a backfill

In the Inital backfill card, select the public.products table to initate a backfill when the sink is created.

Initial backfill card with public.products table selected

Configure Typesense

In the Typesense card, enter your Typesense configuration:

Host: http://host.docker.internal:8108
- If that doesn’t work, your host and port may be http://typesense-server:8108
Collection: products
API Key: my-api-key

You can leave the rest of the defaults.

Create the sink

Give your sink a name, like products-typesense, and click “Create Sink”.As configured, the Typesense collection will first receive a backfill of all rows currently in the products table. Then, it will receive all changes to the products table in real-time.

Query your data in Typesense

With our initial backfill complete, we can now query Typesense for our products collection:

curl -X GET "http://localhost:8108/collections/products/documents/search?q=*" \
  -H "X-TYPESENSE-API-KEY: my-api-key"

This query will return all documents in the products collection.To query for just products matching “avocado”, we can add a name parameter to the query:

curl -X GET "http://localhost:8108/collections/products/documents/search?q=avocado&query_by=name" \
    -H "X-TYPESENSE-API-KEY: my-api-key"

This query returns all documents in the products collection where the name field matches “avocado”.

See changes flow to Typesense

On the new sink’s overview page, you should see the “Health” status turn green, indicating data is flowing to Typesense.Let’s confirm data is flowing by making some changes and searching in Typesense:

Make some changes

Let’s make some changes to the products table and see them flow to Typesense.In your terminal, run the following command to insert a new row into the products table:

docker exec -i sequin-sequin_postgres-1 \
  psql -U postgres -d sequin_playground -c \
  "insert into products (name, price) values ('Organic Honey (16 oz)', 12.99);"

After a few seconds, search for the new product in Typesense:

curl -X GET "http://localhost:8108/collections/products/documents/search?q=honey&query_by=name" \
  -H "X-TYPESENSE-API-KEY: my-api-key"

You should see the new product appear in the search results.Feel free to try other changes:

Update a product's price

docker exec -i sequin-sequin_postgres-1 \
  psql -U postgres -d sequin_playground -c \
  "update products set price = 7.99 where name = 'Avocados (3 pack)';"

Change a product's name

docker exec -i sequin-sequin_postgres-1 \
  psql -U postgres -d sequin_playground -c \
  "update products set name = 'Organic Avocados (3 pack)' where name = 'Avocados (3 pack)';"

Delete a product

docker exec -i sequin-sequin_postgres-1 \
  psql -U postgres -d sequin_playground -c \
  "delete from products where name = 'Blueberries (6 oz)';"

Each change will be reflected in Typesense within a few seconds. Try searching for the modified or deleted products to verify the changes.

Try fuzzy search

Typesense supports fuzzy search with typo tolerance. Try searching with a typo:

curl -X GET "http://localhost:8108/collections/products/documents/search?q=steak&query_by=name&num_typos=1" \
  -H "X-TYPESENSE-API-KEY: my-api-key"

Even with a typo, you should still find relevant products.

Great work!

You’ve successfully:

Created a Typesense collection
Loaded existing data through a backfill
Made changes to the products table
Verified changes are flowing to Typesense
Tested search functionality
Set up a complete Postgres change data capture pipeline

Ready to stream

Now you’re ready to connect your own database to Sequin and start streaming changes:

Guide: Connect Postgres

Connect your Postgres database to Sequin.

Guide: Setting up a Typesense sink

Setup a Typesense sink to keep your search index in sync.

Get started

Sink setup guides

How-to guides

Concepts

Reference

Database setup guides

Tutorials

Get started with Typesense

Run Sequin

Login

View the playground database

Create a Typesense Collection

Create a Typesense Sink

Query your data in Typesense

See changes flow to Typesense

Ready to stream

Guide: Connect Postgres

Guide: Setting up a Typesense sink

Run Sequin

Login

View the playground database

Create a Typesense Collection

Create a Typesense Sink

Query your data in Typesense

See changes flow to Typesense

​Ready to stream

Guide: Connect Postgres

Guide: Setting up a Typesense sink

Ready to stream