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Google Cloud Storage (GCS)

Availability
Available CoreAvailable StandardAvailable PlusAvailable ProAvailable Enterprise FlexAvailable Self-Managed EnterpriseAvailable PyAirbyte
Support Level
Airbyte
Connector Version
0.10.7 (last updated 16 days ago)
CDK Version
7.10.1
Sync Success Rate
Usage Rate
Definition ID
2a8c41ae-8c23-4be0-a73f-2ab10ca1a820

This page contains the setup guide and reference information for the Google Cloud Storage (GCS) source connector.

info

Cloud storage may incur egress costs. Egress refers to data that is transferred out of the cloud storage system, such as when you download files or access them from a different location. For more information, see the Google Cloud Storage pricing guide.

Prerequisites​

  • A Google Cloud account with a service account that has read access to the target GCS bucket, or a Google account that can authenticate via OAuth
  • The service account must have the Storage Object Viewer (roles/storage.objectViewer) role on the bucket, or equivalent permissions (storage.objects.get and storage.objects.list). For more details, see the GCS IAM documentation.
  • A GCS bucket containing the files you want to replicate

Setup guide​

Create a service account​

First, select an existing project or create a new project in the Google Cloud Console:

  1. Sign in to your Google account.
  2. Go to the Service Accounts page.
  3. Click Create service account.
  4. Create a JSON key file for the service account. The contents of this file will be provided as the Service Account Information in the connector configuration.

Grant permission to GCS​

Grant the service account read access to your target bucket. At minimum, assign the Storage Object Viewer (roles/storage.objectViewer) role. See Using IAM permissions for details.

Set up the connector in Airbyte​

  1. Log in to your Airbyte account.
  2. Click Sources and then click + New source.
  3. On the Set up the source page, select Google Cloud Storage (GCS) from the Source type dropdown.
  4. Enter a name for the connector.
  5. Select an authorization type:
    • Authenticate via Google (OAuth): Click Sign in with Google and complete the authentication workflow.
    • Service Account Information: Paste the service account JSON key into the Service Account Information field.
  6. Enter your GCS bucket name in the Bucket field.
  7. Add a stream:
    1. Enter a Name for the stream.
    2. In the Format box, use the dropdown menu to select the format of the files you'd like to replicate. Toggle the Optional fields button within the Format box to enter additional configurations based on the selected format. For a detailed breakdown of these settings, refer to the File Format Settings section.
    3. Optionally, enter the Globs which dictate which files to sync. Globs use glob-style pattern matching to select specific files for replication. If you are replicating all the files within your bucket, use ** as the pattern. For more precise pattern matching options, refer to the Path Patterns section.
    4. Optionally, enter an Input schema to enforce a specific schema. By default, this value is set to {} and will automatically infer the schema from the files you are replicating. For details on providing a custom schema, refer to the User Schema section.
  8. Optionally, configure the Start Date parameter that marks a starting date and time in UTC for data replication. Any files that have not been modified since this specified date/time will not be replicated. Use the provided datepicker or enter the desired date programmatically in the format YYYY-MM-DDTHH:mm:ssZ. Leaving this field blank replicates data from all files that have not been excluded by the Path Pattern and Path Prefix.
  9. Click Set up source and wait for the tests to complete.

File URLs​

The GCS source connector uses signed URLs to work with files when authenticated with a service account, and gs:// URIs when authenticated via Google OAuth.

File URLs are stored in the connection state. If you change the authorization type and use incremental sync, the next sync will not use the old state and will re-read all files in full refresh mode. Subsequent syncs will be incremental as expected.

Path Patterns​

tip

Path patterns use wcmatch.glob syntax with GLOBSTAR and SPLIT flags enabled.

This connector can sync multiple files by using glob-style patterns, rather than requiring a specific path for every file. This enables:

  • Referencing many files with just one pattern, e.g. ** would indicate every file in the bucket.
  • Referencing future files that don't exist yet and therefore don't have a specific path.

You must provide a path pattern. You can also provide multiple patterns split with | for more complex directory layouts.

Each path pattern is a reference from the root of the bucket, so don't include the bucket name itself in the patterns.

Some example patterns:

  • ** : match everything.
  • **/*.csv : match all files with specific extension.
  • myFolder/**/*.csv : match all CSV files anywhere under myFolder.
  • */** : match everything at least one folder deep.
  • */*/*/** : match everything at least three folders deep.
  • **/file.*|**/file : match every file called "file" with any extension or no extension.
  • x/*/y/* : match all files that sit in sub-folder x, then any folder, then folder y.
  • **/prefix*.csv : match all CSV files with specific prefix.
  • **/prefix*.parquet : match all Parquet files with specific prefix.

Let's look at a specific example, matching the following folder layout (MyFolder is the folder specified in the connector config as the root folder, which the patterns are relative to):

MyFolder
    -> log_files
    -> some_table_files
        -> part1.csv
        -> part2.csv
    -> images
    -> more_table_files
        -> part3.csv
    -> extras
        -> misc
            -> another_part1.csv

We want to pick up part1.csv, part2.csv and part3.csv (excluding another_part1.csv for now). We could do this a few different ways:

  • We could pick up every CSV file called "partX" with the single pattern **/part*.csv.
  • To be a bit more robust, we could use the dual pattern some_table_files/*.csv|more_table_files/*.csv to pick up relevant files only from those exact folders.
  • We could achieve the above in a single pattern by using the pattern *table_files/*.csv. This could however cause problems in the future if new unexpected folders started being created.
  • We can also recursively wildcard, so adding the pattern extras/**/*.csv would pick up any CSV files nested in folders below "extras", such as "extras/misc/another_part1.csv".

As you can probably tell, there are many ways to achieve the same goal with path patterns. We recommend using a pattern that ensures clarity and is robust against future additions to the directory structure.

User Schema​

When using the Avro, JSONL, CSV, or Parquet format, you can provide a schema to use for the output stream. Note that this doesn't apply to the experimental Document file type format.

Providing a schema allows for more control over the output of this stream. Without a provided schema, columns and datatypes will be inferred from the first created file in the bucket matching your path pattern and suffix. This will probably be fine in most cases but there may be situations you want to enforce a schema instead, e.g.:

  • You only care about a specific known subset of the columns. The other columns would all still be included, but packed into the _ab_additional_properties map.
  • Your initial dataset is quite small in terms of number of records, and you think the automatic type inference from this sample might not be representative of the data in the future.
  • You want to purposely define types for every column.
  • You know the names of columns that will be added to future data and want to include these in the core schema as columns rather than have them appear in the _ab_additional_properties map.

The schema must be provided as valid JSON as a map of {"column": "datatype"} where each datatype is one of:

  • string
  • number
  • integer
  • object
  • array
  • boolean
  • null

For example:

  • {"id": "integer", "location": "string", "longitude": "number", "latitude": "number"}
  • {"username": "string", "friends": "array", "information": "object"}

File Format Settings​

Avro​

  • Convert Double Fields to Strings: Whether to convert double fields to strings. This is recommended if you have decimal numbers with a high degree of precision because there can be a loss precision when handling floating point numbers.

CSV​

Since CSV files are effectively plain text, providing specific reader options is often required for correct parsing of the files. These settings are applied when a CSV is created or exported so please ensure that this process happens consistently over time.

  • Header Definition: How headers will be defined. User Provided assumes the CSV does not have a header row and uses the headers provided and Autogenerated assumes the CSV does not have a header row and the CDK will generate headers using for f{i} where i is the index starting from 0. Else, the default behavior is to use the header from the CSV file. If a user wants to autogenerate or provide column names for a CSV having headers, they can set a value for the "Skip rows before header" option to ignore the header row.
  • Delimiter: Even though CSV is an acronym for Comma Separated Values, it is used more generally as a term for flat file data that may or may not be comma separated. The delimiter field lets you specify which character acts as the separator. To use tab-delimiters, you can set this value to \t. By default, this value is set to ,.
  • Double Quote: This option determines whether two quotes in a quoted CSV value denote a single quote in the data. Set to True by default.
  • Encoding: Some data may use a different character set, typically when different alphabets are involved. See the list of allowable encodings here. By default, this is set to utf8.
  • Escape Character: An escape character can be used to prefix a reserved character and ensure correct parsing. A commonly used character is the backslash (\). For example, given the following data:
Product,Description,Price
Jeans,"Navy Blue, Bootcut, 34\"",49.99

The backslash (\) is used directly before the second double quote (") to indicate that it is not the closing quote for the field, but rather a literal double quote character that should be included in the value (in this example, denoting the size of the jeans in inches: 34" ).

Leaving this field blank (default option) will disallow escaping.

  • False Values: A set of case-sensitive strings that should be interpreted as false values.
  • Null Values: A set of case-sensitive strings that should be interpreted as null values. For example, if the value 'NA' should be interpreted as null, enter 'NA' in this field.
  • Quote Character: In some cases, data values may contain instances of reserved characters, like a comma if that's the delimiter. CSVs can handle this by wrapping a value in defined quote characters so that on read it can parse it correctly. By default, this is set to ".
  • Skip Rows After Header: The number of rows to skip after the header row.
  • Skip Rows Before Header: The number of rows to skip before the header row.
  • Strings Can Be Null: Whether strings can be interpreted as null values. If true, strings that match the null_values set will be interpreted as null. If false, strings that match the null_values set will be interpreted as the string itself.
  • True Values: A set of case-sensitive strings that should be interpreted as true values.

JSONL​

  • Schemaless: When enabled, syncs will not validate or structure records against the stream's schema.

Parquet​

  • Convert Double Fields to Strings: Whether to convert double fields to strings. This is recommended if you have decimal numbers with a high degree of precision because there can be a loss precision when handling floating point numbers.

Unstructured document format​

  • Parsing Strategy: The strategy used to parse documents. fast extracts text directly from the document which doesn't work for all files. ocr_only is more reliable, but slower. hi_res is the most reliable, but requires an API key and a hosted instance of unstructured and can't be used with local mode. See the unstructured.io documentation for more details.
  • Processing: Processing configuration. Options:
    • Local - Process files locally, supporting fast and ocr modes. This is the default option.
    • Via API - Process files via an API, using the hi_res mode. This option is useful for increased performance and accuracy, but requires an API key and a hosted instance of unstructured.
  • Skip Unprocessable Files: If true, skip files that cannot be parsed and pass the error message along as the _ab_source_file_parse_error field. If false, fail the sync.
  • Schemaless: When enabled, syncs will not validate or structure records against the stream's schema.

Excel​

  • Schemaless: When enabled, syncs will not validate or structure records against the stream's schema.

Supported sync modes​

The Google Cloud Storage (GCS) source connector supports the following sync modes:

FeatureSupported?Notes
Full Refresh SyncYes
Incremental SyncYes

Supported file formats​

This connector supports the following file formats:

  • Avro
  • CSV
  • Excel
  • JSONL
  • Parquet
  • Unstructured document format

The connector also supports reading files compressed with gzip (.gz) or bzip2 (.bz2), and can extract and process files from ZIP (.zip) archives. ZIP archives containing files in any of the supported formats are automatically extracted during sync.

Reference​

Config fields reference

Field
Type
Property name
string
bucket
object
credentials
array<object>
streams
object
delivery_method
string
start_date

Changelog​

Expand to review
VersionDatePull RequestSubject
0.10.92026-03-1974779Fix ZIP file detection for files with compound extensions (e.g. .csv.zip)
0.10.82026-03-1974781Fix records quadratic duplication when extracting ZIP archives
0.10.72026-03-0370287Update dependencies
0.10.62026-02-1373332Fix zip file extraction failing with DeliverRawFiles has no attribute delivery_type error
0.10.52025-11-2569913Update dependencies
0.10.42025-11-1869426Update dependencies
0.10.32025-11-1169270Update dependencies
0.10.22025-11-0469159Update dependencies
0.10.12025-10-2969054Update dependencies
0.10.02025-10-2768619Update dependencies
0.9.22025-10-2168330Update dependencies
0.9.12025-10-1468032Update dependencies
0.9.02025-10-0767340Promoting release candidate 0.9.0-rc.1 to a main version.
0.9.0-rc.12025-10-0666671Update to latest airbyte cdk
0.8.312025-09-3066303Update dependencies
0.8.302025-09-0966088Update dependencies
0.8.292025-08-2365389Update dependencies
0.8.282025-08-1664980Update dependencies
0.8.272025-08-0964627Update dependencies
0.8.262025-08-0264367Update dependencies
0.8.252025-07-2663951Update dependencies
0.8.242025-07-1963564Update dependencies
0.8.232025-07-1262985Update dependencies
0.8.222025-07-0562822Update dependencies
0.8.212025-06-2861274Update dependencies
0.8.202025-05-2760868Update dependencies
0.8.192025-05-2460392Update dependencies
0.8.182025-05-1060012Update dependencies
0.8.172025-05-0359443Update dependencies
0.8.162025-04-2658915Update dependencies
0.8.152025-04-1958312Update dependencies
0.8.142025-04-1257772Update dependencies
0.8.132025-04-0557213Update dependencies
0.8.122025-03-2956520Update dependencies
0.8.112025-03-2255956Update dependencies
0.8.102025-03-0855314Update dependencies
0.8.92025-03-0154973Update dependencies
0.8.82025-02-2554677Fix io.UnsupportedOperation: underlying stream is not seekable
0.8.72025-02-2254458Update dependencies
0.8.62025-02-1553712Update dependencies
0.8.52025-02-0853365Update dependencies
0.8.42025-02-0152379Update dependencies
0.8.32025-01-1849174Update dependencies
0.8.22024-11-2548647Starting with this version, the Docker image is now rootless. Please note that this and future versions will not be compatible with Airbyte versions earlier than 0.64
0.8.12024-10-2845923Update logging
0.8.02024-10-2845414Add support for OAuth authentication
0.7.42024-10-1246858Update dependencies
0.7.32024-10-0546458Update dependencies
0.7.22024-09-2846178Update dependencies
0.7.12024-09-2445850Add integration tests
0.7.02024-09-2445671Add .zip files support
0.6.92024-09-2145798Update dependencies
0.6.82024-09-1945092Update CDK v5; Fix OSError not raised in stream_reader.open_file
0.6.72024-09-1445492Update dependencies
0.6.62024-09-0745232Update dependencies
0.6.52024-08-3145010Update dependencies
0.6.42024-08-2744796Fix empty list of globs when prefix empty
0.6.32024-08-2644781Set file signature URL expiration limit default to max
0.6.22024-08-2444733Update dependencies
0.6.12024-08-1744285Update dependencies
0.6.02024-08-1544015Add support for all FileBasedSpec file types
0.5.02024-08-1444070Update CDK v4 and Python 3.10 dependencies
0.4.152024-08-1243733Update dependencies
0.4.142024-08-1043512Update dependencies
0.4.132024-08-0343236Update dependencies
0.4.122024-07-2742693Update dependencies
0.4.112024-07-2042312Update dependencies
0.4.102024-07-1341865Update dependencies
0.4.92024-07-1041430Update dependencies
0.4.82024-07-0941148Update dependencies
0.4.72024-07-0641015Update dependencies
0.4.62024-06-2640540Update dependencies
0.4.52024-06-2540391Update dependencies
0.4.42024-06-2440234Update dependencies
0.4.32024-06-2240089Update dependencies
0.4.22024-06-0639255[autopull] Upgrade base image to v1.2.2
0.4.12024-05-2938696Avoid error on empty stream when running discover
0.4.02024-03-2136373Add Gzip and Bzip compression support. Manage dependencies with Poetry.
0.3.72024-02-0634936Bump CDK version to avoid missing SyncMode errors
0.3.62024-01-3034681Unpin CDK version to make compatible with the Concurrent CDK
0.3.52024-01-3034661Pin CDK version until upgrade for compatibility with the Concurrent CDK
0.3.42024-01-1134158Fix issue in stream reader for document file type parser
0.3.32023-12-0633187Bump CDK version to hide source-defined primary key
0.3.22023-11-1632608Improve document file type parser
0.3.12023-11-1332357Improve spec schema
0.3.02023-10-1131212Migrated to file based CDK
0.2.02023-06-2627725License Update: Elv2
0.1.02023-02-1623186New Source: GCS
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