Finance · Source connector
Yahoo Finance ELT Connector
Extract brings Yahoo Finance finance data into data warehouses and databases for analysis with the rest of your business data. Teams use it to reconcile financial activity and monitor changes in business performance. Flexible scheduling keeps reporting current for routine analysis and time-sensitive decisions.
View setup guide
Use cases
What teams use this connector for
Financial reconciliation
Compare Yahoo Finance transactions with accounting and operational records to investigate discrepancies.
Revenue and cash-flow analysis
Use Yahoo Finance data to monitor revenue, payment, and cash-flow trends over time.
Customer value modeling
Combine Yahoo Finance financial activity with customer data to calculate value and retention metrics.
Flexible reporting cadence
Refresh Yahoo Finance reporting every 15 minutes, hourly, daily, or on a custom schedule as business needs change.
Warehouse and database analysis
Use Extract to make Yahoo Finance finance data available in data warehouses and databases such as Snowflake, BigQuery, Redshift, and PostgreSQL for governed analysis.
Connector data
Available streams
| Stream | Description | Sync mode |
|---|---|---|
dividends | Fields include symbol, date, amount, currency. | Incremental |
prices_daily | Fields include symbol, date, open, high. | Incremental |
splits | Fields include symbol, date, numerator, denominator. | Incremental |
Schema
Data model at a glance
dividends
symbolstringdatestringamountnumbercurrencystring
prices_daily
symbolstringdatestringopennumberhighnumberlownumberclosenumberadjclosenumbervolumeinteger
splits
symbolstringdatestringnumeratornumberdenominatornumbersplit_ratiostring
No verified relationships are available in this schema preview.
Connector pairings
Popular destinations
Commonly paired with Yahoo Finance in Extract workflows.
Why Extract
Why Extract for Yahoo Finance
- Rust-native performanceUse Rust-native data movement to refresh Yahoo Finance reporting every 15 minutes, hourly, daily, or on a custom schedule as volume grows.
- Full run transparencyInspect Yahoo Finance API activity, execution steps, and timing in Extract's run-level logs when data needs review.
- ELT + Reverse ETL in oneCombine Yahoo Finance data with customer and finance models, then send approved outputs through a separately configured Reverse ETL destination.
FAQ
Frequently asked questions
How does Extract handle incremental and full Yahoo Finance syncs?
An incremental sync processes only new or changed data since a stored checkpoint or new date partition, while a full sync processes the complete selected dataset or date range again. By avoiding repeated processing and writes for the full dataset, incremental syncs can reduce destination database updates and warehouse compute costs. Stream schemas define partition-based extraction. Behavior varies by stream and configuration. Extract records run details so teams can verify each sync.
Can I backfill historical Yahoo Finance data with Extract?
Historical coverage for Yahoo Finance: Backfill (Days) (backfill): Number of days to re-sync on every run. Use the setup guide and run details to confirm the available source records and selected settings.
How can teams monitor Yahoo Finance data quality and freshness?
Compare expected reporting periods and record totals in your models, then use Extract's run-level logs to inspect Yahoo Finance API activity, execution steps, and timing. This helps teams distinguish a source-data delay from a failed or incomplete run.
How often can Extract sync data from Yahoo Finance?
Extract supports schedules every 15 minutes, hourly, daily, or on a custom cadence. Teams can choose a frequency that matches routine reporting, time-sensitive monitoring, or operational activation needs.
What does the Yahoo Finance data model look like in the destination?
The Available streams table describes the datasets Extract can read from Yahoo Finance. The inline schema previews entities and fields. Only relationships verified from the exported schema are shown. Use the full schema link for more details.