add risingwave to manual replication and link to it from mssql server migration guide

apps/docs/content/guides/database/replication/manual-replication-faq.mdx

@@ -40,5 +40,6 @@ Some of the more important options to be aware of are:
 - `max_slot_wal_keep_size` - Maximum size of WAL files that replication slots are allowed to retain
 - `wal_keep_size` - Minimum number of past WAL files to keep for standby servers
 - `max_wal_senders` - Maximum number of concurrent connections from standby servers or streaming backup clients
+- `wal_sender_timeout` - Maximum time to wait for WAL sender to send WAL
 
 These settings help ensure your replication slots don't run out of space and that replicas can reconnect without requiring a full re-sync.

apps/docs/content/guides/database/replication/manual-replication-setup.mdx

@@ -31,6 +31,8 @@ If you are running Postgres 17 or higher, you can create a new user and grant th
 
 If you are replicating to an external system and using any of the tools below, check their documentation first. Additional information is provided where the setup with Supabase can vary.
 
+The settings of your Supabase project can be modified to support high volume replication, read the [customising postgres config](/docs/guides/platform/custom-postgres-config) guide for more information on the settings available.
+
 <Tabs
   scrollable
   size="small"
@@ -107,4 +109,10 @@ You can follow those steps with the following modifications:
 
 </TabPanel>
 
+<TabPanel id="risingwave" label="Rising Wave">
+
+Rising Wave has the following [documentation](https://docs.risingwave.com/ingestion/sources/postgresql/supabase#set-up-supabase-postgresql) on replicating to and from Supabase.
+
+</TabPanel>
+
 </Tabs>

apps/docs/content/guides/database/replication/replication-setup.mdx

@@ -150,7 +150,6 @@ First, create an analytics bucket to store your replicated data:
      src="/docs/img/database/replication/replication-iceberg-details.png"
      zoomable
    />
-
    - **Name**: A unique name for your bucket (e.g., `analytics_warehouse`)
    - **Region**: Select the region where your data will be stored
 
@@ -173,13 +172,11 @@ First, create an analytics bucket to store your replicated data:
    />
 
 3. Configure the general settings:
-
    - **Destination name**: A name to identify this destination (e.g., "Analytics Warehouse")
    - **Publication**: The publication to replicate data from (created in [Step 1](#step-1-create-a-postgres-publication))
    - **Destination type**: Select **Analytics Buckets**
 
 4. Configure Analytics Buckets settings:
-
    - **Bucket**: The name of your analytics bucket from Step 1
    - **Namespace**: The schema name where your tables will be replicated (e.g., `public`)
    - **Catalog Token**: Authentication token from Step 1
@@ -187,7 +184,6 @@ First, create an analytics bucket to store your replicated data:
    - **S3 Secret Access Key**: Secret key from Step 1
 
 5. Configure **Advanced Settings** (optional):
-
    - **Batch wait time (milliseconds)**: How long to wait for more changes before sending a batch. Default is recommended for optimal performance.
 
 6. Click **Create and start** to begin replication
@@ -233,21 +229,18 @@ Before configuring BigQuery as a destination, set up the following in Google Clo
 1. **Google Cloud Platform (GCP) account**: [Sign up for GCP](https://cloud.google.com/gcp) if you don't have one
 
 2. **BigQuery dataset**: Create a [BigQuery dataset](https://cloud.google.com/bigquery/docs/datasets-intro) in your GCP project
-
    - Open the BigQuery console in GCP
    - Select your project
    - Click "Create Dataset"
    - Provide a dataset ID (e.g., `supabase_replication`)
 
 3. **GCP service account key**: Create a [service account](https://cloud.google.com/iam/docs/keys-create-delete) with appropriate permissions:
-
    - Go to IAM & Admin → Service Accounts
    - Click "Create Service Account"
    - Grant the **BigQuery Data Editor** role
    - Create and download the JSON key file
 
    Required permissions:
-
    - `bigquery.datasets.get`
    - `bigquery.tables.create`
    - `bigquery.tables.get`
@@ -267,13 +260,11 @@ Before configuring BigQuery as a destination, set up the following in Google Clo
    />
 
 3. Configure the general settings:
-
    - **Destination name**: A name to identify this destination (e.g., "BigQuery Warehouse")
    - **Publication**: The publication to replicate data from (created in [Step 1](#step-1-create-a-postgres-publication))
    - **Destination type**: Select **BigQuery**
 
 4. Configure BigQuery-specific settings:
-
    - **Project ID**: Your BigQuery project identifier (found in the GCP Console)
    - **Dataset ID**: The name of your BigQuery dataset (without the project ID)
 
@@ -286,7 +277,6 @@ Before configuring BigQuery as a destination, set up the following in Google Clo
    - **Service Account Key**: Your GCP service account key in JSON format (from Step 1)
 
 5. Configure **Advanced Settings** (optional):
-
    - **Batch wait time (milliseconds)**: How long to wait for more changes before sending a batch. Default is recommended for optimal performance.
 
 6. Click **Create and start** to begin replication

apps/docs/content/guides/platform/migrating-to-supabase/mssql.mdx

@@ -78,3 +78,9 @@ Alternatively, you can use [pgloader](https://github.com/dimitri/pgloader), a fl
 ## Enterprise
 
 [Contact us](https://forms.supabase.com/enterprise) if you need more help migrating your project.
+
+### Other tools
+
+Many Change Data Capture (CDC) tools are available for MSSQL, allowing you to add Microsoft SQL Server as a data source and Supabase as a destination.
+
+For more information, read the [Manual Replication](/docs/guides/database/replication/manual-replication-setup)