Docs: Add Estuary as a data ingestion option

docs/integrations/data-ingestion/data-ingestion-index.md

@@ -23,6 +23,7 @@ For more information check out the pages below:
 | [BladePipe](/integrations/bladepipe)                         | A real-time end-to-end data integration tool with sub-second latency, boosting seamless data flow across platforms.                                                                                |
 | [dbt](/integrations/dbt)                                         | Enables analytics engineers to transform data in their warehouses by simply writing select statements.                                                                                                                                |
 | [dlt](/integrations/data-ingestion/etl-tools/dlt-and-clickhouse) | An open-source library that you can add to your Python scripts to load data from various and often messy data sources into well-structured, live datasets.                                                                            |
+| [Estuary](/integrations/estuary)                                 | A right-time data platform that enables millisecond-latency ETL pipelines with flexible deployment options.                                    |
 | [Fivetran](/integrations/fivetran)                               | An automated data movement platform moving data out of, into and across your cloud data platforms.                                                                                                                                    |
 | [NiFi](/integrations/nifi)                                       | An open-source workflow management software designed to automate data flow between software systems.                                                                                                                                  |
 | [Vector](/integrations/vector)                                   | A high-performance observability data pipeline that puts organizations in control of their observability data.                                                                                                                        |

docs/integrations/data-ingestion/etl-tools/estuary.md

@@ -0,0 +1,110 @@
+---
+sidebar_label: 'Estuary'
+slug: /integrations/estuary
+description: 'Stream a variety of sources into ClickHouse with an Estuary integration'
+title: 'Connect Estuary with ClickHouse'
+doc_type: 'guide'
+integration:
+  - support_level: 'partner'
+  - category: 'data_ingestion'
+  - website: 'https://estuary.dev'
+keywords: ['estuary', 'data ingestion', 'etl', 'pipeline', 'data integration', 'clickpipes']
+---
+
+import PartnerBadge from '@theme/badges/PartnerBadge';
+
+# Connect Estuary with ClickHouse
+
+<PartnerBadge/>
+
+[Estuary](https://estuary.dev/) is a right-time data platform that flexibly combines real-time and batch data in simple-to-setup ETL pipelines. With enterprise-grade security and deployment options, Estuary unlocks durable data flows from SaaS, database, and streaming sources to a variety of destinations, including ClickHouse.
+
+Estuary connects with ClickHouse via the Kafka ClickPipe. You do not need to maintain your own Kafka ecosystem with this integration.
+
+## Setup guide {#setup-guide}
+
+**Prerequisites**
+
+* An [Estuary account](https://dashboard.estuary.dev/register)
+* One or more [**captures**](https://docs.estuary.dev/concepts/captures/) in Estuary that pull data from your desired source(s)
+* A ClickHouse Cloud account with ClickPipe permissions
+
+<VerticalStepper headerLevel="h3">
+
+### Create an Estuary materialization {#1-create-an-estuary-materialization}
+
+To move data from your source collections in Estuary to ClickHouse, you will first need to create a **materialization**.
+
+1. In Estuary's dashboard, go to the [Destinations](https://dashboard.estuary.dev/materializations) page.
+
+2. Click **+ New Materialization**.
+
+3. Select the **ClickHouse** connector.
+
+4. Fill out details in the Materialization, Endpoint, and Source Collections sections:
+
+   * **Materialization Details:** Provide a unique name for your materialization and choose a data plane (cloud provider and region)
+
+   * **Endpoint Config:** Provide a secure **Auth Token**
+
+   * **Source Collections:** Link an existing **capture** or select data collections to expose to ClickHouse
+
+5. Click **Next** and **Save and Publish**.
+
+6. On the materialization details page, note the full name for your ClickHouse materialization. This will look something like `your-tenant/your-unique-name/dekaf-clickhouse`.
+
+Estuary will start streaming the selected collections as Kafka messages. ClickHouse can access this data via a Kafka ClickPipe using Estuary's broker details and the auth token you provided.
+
+### Enter Kafka connection details {#2-enter-kafka-connection-details}
+
+Set up a new Kafka ClickPipe with ClickHouse and enter connection details:
+
+1. In your ClickHouse Cloud dashboard, select **Data sources**.
+
+2. Create a new **ClickPipe**.
+
+3. Choose **Apache Kafka** as your data source.
+
+4. Enter Kafka connection details using Estuary's broker and registry information:
+
+   * Provide a name for your ClickPipe
+   * For the broker, use: `dekaf.estuary-data.com:9092`
+   * Leave authentication as the default `SASL/PLAIN` option
+   * For the user, enter your full materialization name from Estuary (such as `your-tenant/your-unique-name/dekaf-clickhouse`)
+   * For the password, enter the auth token you provided for your materialization
+
+5. Toggle the schema registry option
+
+   * For your schema URL, use: `https://dekaf.estuary-data.com`
+   * The schema key will be the same as the broker user (your materialization name)
+   * The secret will be the same as the broker password (your auth token)
+
+### Configure incoming data {#3-configure-incoming-data}
+
+1. Select one of your Kafka **topics** (one of your data collections from Estuary).
+
+2. Choose an **offset**.
+
+3. ClickHouse will detect topic messages. You can continue to the **Parse information** section to configure your table information.
+
+4. Choose to create a new table or load data into a matching existing table.
+
+5. Map source fields to table columns, confirming column name, type, and whether it is nullable.
+
+6. In the final **Details and settings** section, you can select permissions for your dedicated database user.
+
+Once you're happy with your configuration, create your ClickPipe.
+
+ClickHouse will provision your new data source and start consuming messages from Estuary. Create as many ClickPipes as you need to stream from all your desired data collections.
+
+</VerticalStepper>
+
+## Additional resources {#additional-resources}
+
+For more on setting up an integration with Estuary, see Estuary's documentation:
+
+* Reference Estuary's [ClickHouse materialization docs](https://docs.estuary.dev/reference/Connectors/materialization-connectors/Dekaf/clickhouse/).
+
+* Estuary exposes data as Kafka messages using **Dekaf**. You can learn more about Dekaf [here](https://docs.estuary.dev/guides/dekaf_reading_collections_from_kafka/).
+
+* To see a list of sources that you can stream into ClickHouse with Estuary, check out [Estuary's capture connectors](https://docs.estuary.dev/reference/Connectors/capture-connectors/).

sidebars.js

@@ -1022,6 +1022,7 @@ const sidebars = {
           ],
         },
         'integrations/data-ingestion/etl-tools/dlt-and-clickhouse',
+        'integrations/data-ingestion/etl-tools/estuary',
         'integrations/data-ingestion/etl-tools/fivetran/index',
         'integrations/data-ingestion/etl-tools/nifi-and-clickhouse',
         'integrations/data-ingestion/etl-tools/vector-to-clickhouse',