Toast to Apache Iceberg integration
Connect Toast to Apache Iceberg and automatically sync your application data. Weld extracts data from Toast, loads it into Apache Iceberg, and lets you transform the data using SQL or dbt, no custom scripts required.
Source
WarehouseSourceToastConnected- restaurant13 cols
- order73 cols
- cash_entry25 cols
- service_area8 cols
- dining_option7 cols
- cash_drawer6 cols
- Extract
- Load
- Keep in sync
DestinationApache IcebergReady- toast.restaurantSynced
- toast.orderSyncing
- toast.cash_entrySynced
- toast.service_areaSynced
- toast.dining_optionSynced
- toast.cash_drawerSynced
- Toast tables
- 67
- fields, typed
- 1,021
- relationships kept
- 47
- agent context included
- MCP
Trusted by data and AI teams
How to set up Toast to Apache Iceberg in Weld.
In the app, with the API or an agent.
New connectionToastAuthorisedWhy sync Toast to Apache Iceberg?
Ready for analysis.
Centralizing your Toast data in Apache Iceberg lets you join it with other data sources for cross-platform analytics and deeper insights.
Build reliable dashboards and reports by querying Toast data directly in Apache Iceberg using SQL or your preferred BI tool.
Centralized data warehouse
Bring Toast data into Apache Iceberg alongside other sources to create a single source of truth for your organization.
Automated reporting
Replace manual exports and spreadsheet-based reporting with automated pipelines from Toast to Apache Iceberg. Connect BI tools like Looker, Metabase, or Power BI.
What data can you sync?
Every Toast table, keys intact.
Weld syncs the objects the Toast connector exposes into Apache Iceberg, and you choose which tables and fields to include. The connector's docs list what is available.
- restaurant
- order
- cash_entry
- service_area
- dining_option
- cash_drawer
- discount
- tax_rate
- table
- revenue_center
- void_reason
- order_check_selection_modifier
- order_check_selection
- service_charge
- prep_station
- no_sale_reason
- payout_reason
- printer
- restaurant_service
- order_check_payment
- order_check_selection_applied_discount
- order_check_applied_discount
- time_entry
- order_check_applied_service_charge
- shift
- order_check_selection_applied_tax
- break_type
- job
- cash_deposit
- inventory
- and 37 more
Ask your agent.
It queries Apache Iceberg for you.
Connect Claude, Cursor, ChatGPT or your own agent to Weld over MCP. It reads the Toast context, finds the tables it needs and runs the query in Apache Iceberg.
How many menu_item_tax_rate rows do we have per tax_rate? Use our Toast data in Apache Iceberg.
Reading the Toast context first, so the query uses the right tables and keys.
Technical considerations.
What to expect.
- Incremental syncing
- Weld uses incremental syncing where supported by the Toast API, loading only new and updated records to minimize data transfer and warehouse costs.
- Schema handling
- Weld automatically manages schema changes. If Toast adds new fields, they're detected and added to the corresponding Apache Iceberg tables.
- Data freshness
- Sync frequency depends on your Weld plan. Most connectors support schedules from every 5 minutes up to daily intervals.
- Security
- All data is encrypted in transit (TLS) and at rest. Weld is SOC 2 Type II compliant and supports IP whitelisting for database connections.
Keep reading.
Guides, docs and schema.
Common questions.
About Toast to Apache Iceberg.
Start syncing Toast to Apache Iceberg.
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SourceWarehouse
