> ## Documentation Index > Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt > Use this file to discover all available pages before exploring further. > Stream data into ClickHouse using Airbyte data pipelines # Connect Airbyte to ClickHouse export const PartnerBadge = () => { return
Partner Integration
; }; export const Image = ({img, alt, size = "lg"}) => { const normalizedSize = ["sm", "md", "lg"].includes(size) ? size : "lg"; return
{alt}
; }; Please note that the Airbyte source and destination for ClickHouse are currently in Alpha status and not suitable for moving large datasets (> 10 million rows) Airbyte is an open-source data integration platform. It allows the creation of ELT data pipelines and is shipped with more than 140 out-of-the-box connectors. This step-by-step tutorial shows how to connect Airbyte to ClickHouse as a destination and load a sample dataset. 1. Airbyte runs on Docker and uses `docker-compose`. Make sure to download and install the latest versions of Docker. 2. Deploy Airbyte by cloning the official Github repository and running `docker-compose up` in your favorite terminal: ```bash theme={null} git clone https://github.com/airbytehq/airbyte.git --depth=1 cd airbyte ./run-ab-platform.sh ``` 3. Once you see the Airbyte banner in your terminal, you can connect to localhost:8000 Airbyte banner Alternatively, you can signup and use Airbyte Cloud In this section, we will display how to add a ClickHouse instance as a destination. 1. Start your ClickHouse server (Airbyte is compatible with ClickHouse version `21.8.10.19` or above) or login to your ClickHouse cloud account: ```bash theme={null} clickhouse-server start ``` 2. Within Airbyte, select the "Destinations" page and add a new destination: Add a destination in Airbyte 3. Select ClickHouse from the "Destination type" drop-down list, and Fill out the "Set up the destination" form by providing your ClickHouse hostname and ports, database name, username and password and select if it's an SSL connection (equivalent to the `--secure` flag in the `clickhouse-client`): ClickHouse destination creation in Airbyte 4. Congratulations! you have now added ClickHouse as a destination in Airbyte. In order to use ClickHouse as a destination, the user you'll use need to have the permissions to create databases, tables and insert rows. We recommend creating a dedicated user for Airbyte (eg. `my_airbyte_user`) with the following permissions: ```sql theme={null} CREATE USER 'my_airbyte_user'@'%' IDENTIFIED BY 'your_password_here'; GRANT CREATE ON * TO my_airbyte_user; ``` The example dataset we will use is the New York City Taxi Data (on Github). For this tutorial, we will use a subset of this dataset which corresponds to the month of Jan 2022. 1. Within Airbyte, select the "Sources" page and add a new source of type file. Add a source in Airbyte 2. Fill out the "Set up the source" form by naming the source and providing the URL of the NYC Taxi Jan 2022 file (see below). Make sure to pick `parquet` as file format, `HTTPS Public Web` as Storage Provider and `nyc_taxi_2022` as Dataset Name. ```text theme={null} https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2022-01.parquet ``` ClickHouse source creation in Airbyte 3. Congratulations! You have now added a source file in Airbyte. 1. Within Airbyte, select the "Connections" page and add a new connection Add a connection in Airbyte 2. Select "Use existing source" and select the New York City Taxi Data, the select "Use existing destination" and select you ClickHouse instance. 3. Fill out the "Set up the connection" form by choosing a Replication Frequency (we will use `manual` for this tutorial) and select `nyc_taxi_2022` as the stream you want to sync. Make sure you pick `Normalized Tabular Data` as a Normalization. Connection creation in Airbyte 4. Now that the connection is created, click on "Sync now" to trigger the data loading (since we picked `Manual` as a Replication Frequency) Sync now in Airbyte 5. Your data will start loading, you can expand the view to see Airbyte logs and progress. Once the operation finishes, you'll see a `Completed successfully` message in the logs: Completed successfully 6. Connect to your ClickHouse instance using your preferred SQL Client and check the resulting table: ```sql theme={null} SELECT * FROM nyc_taxi_2022 LIMIT 10 ``` The response should look like: ```response theme={null} Query id: 4f79c106-fe49-4145-8eba-15e1cb36d325 ┌─extra─┬─mta_tax─┬─VendorID─┬─RatecodeID─┬─tip_amount─┬─airport_fee─┬─fare_amount─┬─DOLocationID─┬─PULocationID─┬─payment_type─┬─tolls_amount─┬─total_amount─┬─trip_distance─┬─passenger_count─┬─store_and_fwd_flag─┬─congestion_surcharge─┬─tpep_pickup_datetime─┬─improvement_surcharge─┬─tpep_dropoff_datetime─┬─_airbyte_ab_id───────────────────────┬─────_airbyte_emitted_at─┬─_airbyte_normalized_at─┬─_airbyte_nyc_taxi_2022_hashid────┐ │ 0 │ 0.5 │ 2 │ 1 │ 2.03 │ 0 │ 17 │ 41 │ 162 │ 1 │ 0 │ 22.33 │ 4.25 │ 3 │ N │ 2.5 │ 2022-01-24T16:02:27 │ 0.3 │ 2022-01-24T16:22:23 │ 000022a5-3f14-4217-9938-5657f9041c8a │ 2022-07-19 04:35:31.000 │ 2022-07-19 04:39:20 │ 91F83E2A3AF3CA79E27BD5019FA7EC94 │ │ 3 │ 0.5 │ 1 │ 1 │ 1.75 │ 0 │ 5 │ 186 │ 246 │ 1 │ 0 │ 10.55 │ 0.9 │ 1 │ N │ 2.5 │ 2022-01-22T23:23:05 │ 0.3 │ 2022-01-22T23:27:03 │ 000036b6-1c6a-493b-b585-4713e433b9cd │ 2022-07-19 04:34:53.000 │ 2022-07-19 04:39:20 │ 5522F328014A7234E23F9FC5FA78FA66 │ │ 0 │ 0.5 │ 2 │ 1 │ 7.62 │ 1.25 │ 27 │ 238 │ 70 │ 1 │ 6.55 │ 45.72 │ 9.16 │ 1 │ N │ 2.5 │ 2022-01-22T19:20:37 │ 0.3 │ 2022-01-22T19:40:51 │ 00003c6d-78ad-4288-a79d-00a62d3ca3c5 │ 2022-07-19 04:34:46.000 │ 2022-07-19 04:39:20 │ 449743975782E613109CEE448AFA0AB3 │ │ 0.5 │ 0.5 │ 2 │ 1 │ 0 │ 0 │ 9.5 │ 234 │ 249 │ 1 │ 0 │ 13.3 │ 1.5 │ 1 │ N │ 2.5 │ 2022-01-22T20:13:39 │ 0.3 │ 2022-01-22T20:26:40 │ 000042f6-6f61-498b-85b9-989eaf8b264b │ 2022-07-19 04:34:47.000 │ 2022-07-19 04:39:20 │ 01771AF57922D1279096E5FFE1BD104A │ │ 0 │ 0 │ 2 │ 5 │ 5 │ 0 │ 60 │ 265 │ 90 │ 1 │ 0 │ 65.3 │ 5.59 │ 1 │ N │ 0 │ 2022-01-25T09:28:36 │ 0.3 │ 2022-01-25T09:47:16 │ 00004c25-53a4-4cd4-b012-a34dbc128aeb │ 2022-07-19 04:35:46.000 │ 2022-07-19 04:39:20 │ CDA4831B683D10A7770EB492CC772029 │ │ 0 │ 0.5 │ 2 │ 1 │ 0 │ 0 │ 11.5 │ 68 │ 170 │ 2 │ 0 │ 14.8 │ 2.2 │ 1 │ N │ 2.5 │ 2022-01-25T13:19:26 │ 0.3 │ 2022-01-25T13:36:19 │ 00005c75-c3c8-440c-a8e8-b1bd2b7b7425 │ 2022-07-19 04:35:52.000 │ 2022-07-19 04:39:20 │ 24D75D8AADD488840D78EA658EBDFB41 │ │ 2.5 │ 0.5 │ 1 │ 1 │ 0.88 │ 0 │ 5.5 │ 79 │ 137 │ 1 │ 0 │ 9.68 │ 1.1 │ 1 │ N │ 2.5 │ 2022-01-22T15:45:09 │ 0.3 │ 2022-01-22T15:50:16 │ 0000acc3-e64f-4b58-8e15-dc47ff1685f3 │ 2022-07-19 04:34:37.000 │ 2022-07-19 04:39:20 │ 2BB5B8E849A438E08F7FCF789E7D7E65 │ │ 1.75 │ 0.5 │ 1 │ 1 │ 7.5 │ 1.25 │ 27.5 │ 17 │ 138 │ 1 │ 0 │ 37.55 │ 9 │ 1 │ N │ 0 │ 2022-01-30T21:58:19 │ 0.3 │ 2022-01-30T22:19:30 │ 0000b339-b44b-40b0-99f8-ebbf2092cc5b │ 2022-07-19 04:38:10.000 │ 2022-07-19 04:39:20 │ DCCE79199EF9217CD769EFD5271302FE │ │ 0.5 │ 0.5 │ 2 │ 1 │ 0 │ 0 │ 13 │ 79 │ 140 │ 2 │ 0 │ 16.8 │ 3.19 │ 1 │ N │ 2.5 │ 2022-01-26T20:43:14 │ 0.3 │ 2022-01-26T20:58:08 │ 0000caa8-d46a-4682-bd25-38b2b0b9300b │ 2022-07-19 04:36:36.000 │ 2022-07-19 04:39:20 │ F502BE51809AF36582561B2D037B4DDC │ │ 0 │ 0.5 │ 2 │ 1 │ 1.76 │ 0 │ 5.5 │ 141 │ 237 │ 1 │ 0 │ 10.56 │ 0.72 │ 2 │ N │ 2.5 │ 2022-01-27T15:19:54 │ 0.3 │ 2022-01-27T15:26:23 │ 0000cd63-c71f-4eb9-9c27-09f402fddc76 │ 2022-07-19 04:36:55.000 │ 2022-07-19 04:39:20 │ 8612CDB63E13D70C1D8B34351A7CA00D │ └───────┴─────────┴──────────┴────────────┴────────────┴─────────────┴─────────────┴──────────────┴──────────────┴──────────────┴──────────────┴──────────────┴───────────────┴─────────────────┴────────────────────┴──────────────────────┴──────────────────────┴───────────────────────┴───────────────────────┴──────────────────────────────────────┴─────────────────────────┴────────────────────────┴──────────────────────────────────┘ ``` ```sql theme={null} SELECT count(*) FROM nyc_taxi_2022 ``` The response is: ```response theme={null} Query id: a9172d39-50f7-421e-8330-296de0baa67e ┌─count()─┐ │ 2392428 │ └─────────┘ ``` 7. Notice that Airbyte automatically inferred the data types and added 4 columns to the destination table. These columns are used by Airbyte to manage the replication logic and log the operations. More details are available in the Airbyte official documentation. ```sql theme={null} `_airbyte_ab_id` String, `_airbyte_emitted_at` DateTime64(3, 'GMT'), `_airbyte_normalized_at` DateTime, `_airbyte_nyc_taxi_072021_hashid` String ``` Now that the dataset is loaded on your ClickHouse instance, you can create an new table and use more suitable ClickHouse data types (more details). 8. Congratulations - you have successfully loaded the NYC taxi data into ClickHouse using Airbyte!