These are just some of the queries that you can run on the Stripe data when you connect it to Splitgraph.
Here are all the tables you will be able to access when you use Splitgraph to query Stripe data. We have also listed some useful queries that you can run.
repositories: - namespace: CHANGEME repository: airbyte-stripe # Catalog-specific metadata for the repository. Optional. metadata: readme: text: Readme description: Description of the repository topics: - sample_topic # Data source settings for the repository. Optional. external: # Name of the credential that the plugin uses. This can also be a credential_id if the # credential is already registered on Splitgraph. credential: airbyte-stripe plugin: airbyte-stripe # Plugin-specific parameters matching the plugin's parameters schema params: account_id: '' # REQUIRED. Account ID. Your Stripe account ID (starts with 'acct_', find yours <a href="https://dashboard.stripe.com/settings/account">here</a>). start_date: '2017-01-25T00:00:00Z' # REQUIRED. Replication start date. UTC date and time in the format 2017-01-25T00:00:00Z. Only data generated after this date will be replicated. normalization_mode: basic # Post-ingestion normalization. Whether to normalize raw Airbyte tables. `none` is no normalization, `basic` is Airbyte's basic normalization, `custom` is a custom dbt transformation on the data.. One of none, basic, custom normalization_git_branch: master # dbt model Git branch. Branch or commit hash to use for the normalization dbt project. lookback_window_days: 0 # Lookback Window in days (Optional). When set, the connector will always re-export data from the past N days, where N is the value set here. This is useful if your data is frequently updated after creation. More info <a href="https://docs.airbyte.com/integrations/sources/stripe#requirements">here</a> slice_range: 1 # Data request time increment in days (Optional). The time increment used by the connector when requesting data from the Stripe API. The bigger the value is, the less requests will be made and faster the sync will be. On the other hand, the more seldom the state is persisted. tables: sample_table: # Plugin-specific table parameters matching the plugin's schema options: airbyte_cursor_field:  # Cursor field(s). Fields in this stream to be used as a cursor for incremental replication (overrides Airbyte configuration's cursor_field) airbyte_primary_key_field:  # Primary key field(s). Fields in this stream to be used as a primary key for deduplication (overrides Airbyte configuration's primary_key) # Schema of the table, a list of objects with `name` and `type`. If set to ``, will infer. schema:  # Whether live querying is enabled for the plugin (creates a "live" tag in the # repository proxying to the data source). The plugin must support live querying. is_live: false # Ingestion schedule settings. Disable this if you're using GitHub Actions or other methods # to trigger ingestion. schedule: credentials: airbyte-stripe: # This is the name of this credential that "external" sections can reference. plugin: airbyte-stripe # Credential-specific data matching the plugin's credential schema data: client_secret: '' # REQUIRED. Secret Key. Stripe API key (usually starts with 'sk_live_'; find yours <a href="https://dashboard.stripe.com/apikeys">here</a>). normalization_git_url: '' # dbt model Git URL. For `custom` normalization, a URL to the Git repo with the dbt project, for example,`https://uname:email@example.com/organisation/repository.git`.
Use our splitgraph.yml format to check your Splitgraph configuration into version control, trigger ingestion jobs and manage your data stack like your code.
Splitgraph connects your vast, unrelated data sources and puts them in a single, accessible place.
Splitgraph handles data integration, storage, transformation and discoverability for you. All that remains is adding a BI client.
Focus on building data-driven applications without worrying about where the data will come from.
Splitgraph supports data ingestion from over 100 SaaS services, as well as data federation to over a dozen databases. These are all made queryable over a PostgreSQL-compatible interface.
Splitgraph stores data in a columnar format. This accelerates analytical queries and makes it perfect for dashboards, blogs and other read-intensive use cases.
Read more about Splitgraph’s support for Stripe, including its documentation and sample queries you can run on Stripe data with Splitgraph.
Splitgraph has a PostgreSQL-compatible endpoint that most BI clients can connect to.