Connector

Collect QuickBooks journal entries in Databricks

Load QuickBooks journal entries and the chart of accounts into your own Databricks workspace with a custom OWOX connector. Manual adjustments become rows you can audit, join and run models on.

QuickBooksConnectedA/P Aging Summar…A/R Aging Summar…AccountsBalance Sheet re…
Data MartPublishedone definition
DatabricksRealmReportReportDaily 09:00
Refreshed on a schedule. No exports, no copy-paste.

Get started free

Endpoints

QuickBooks Endpoints

Documentation

26 QuickBooks endpoints you can import. Each lands in its own table in your data warehouse.

S00 · Why

Why bring journal entries into the same place as the rest

Journal entries are where the books are adjusted by hand, which is why they matter at the close and why they are hard to see in reports. Loading them with the accounts into a data warehouse lets you read every adjustment against the account it touched.

  • Audit manual adjustments by date and by account
  • Join entries to the chart of accounts in SQL
  • Feed forecasting or anomaly models from the same tables
QuickBooksEntries, accounts
Finance modelForecasts
OperationsCosts by team
Your data warehouseDatabricksQuickBooksForecastOperationsJoined by idAdjustment postedAccount reviewedOne query lists the adjustments an account received.

S01 · Step 1

Step 1: Connect QuickBooks and pick the fields

Create a Data Mart, choose QuickBooks as the data source and authorize QuickBooks Online with OAuth. Add the company (realm) id, open an endpoint and tick only the fields you need.

  • Journal entries sits beside Accounts among the 26 endpoints
  • A custom connector: the credential and company id are yours
New Data MartChoose a sourceShopifyQuickBooksFacebook AdsAuthorizeConnectedEndpointJournal entriesA/P Aging Summary…A/R Aging Summary…Accounts
Journal entries15 fieldstxn_datetotal_amtdoc_numberprivate_notecurrency_id

S02 · Step 2

Step 2: Load QuickBooks into Databricks

Each endpoint becomes its own table, and refresh settings are set in the Data Mart. Run it and the first load lands as a table in a schema of the main catalog in Databricks. The location is pre-filled from your data storage, and you can change it.

  • Journal entries land in their own table in the main catalog
  • Every run is logged in Run History
DestinationDatabricksCatalogmainSchemaquickbooksTablejournal_entryRun
Run HistoryPendingRunningSuccessIncremental load
Tablemain.quickbooks.journal_entry

S03 · Step 3

Step 3: Get a business-friendly QuickBooks output schema

After the first run you get the output schema: every field with its type. total_amt is documented as the sum of one side of the entry, and the debit and credit lines stay as JSON.

  • The line array holds PostingType, Debit or Credit, to unnest in SQL
  • private_note keeps the preparer's remark
main.quickbooks.journal_entryOutput schemaFieldDescriptiontxn_dateBusiness date of the…total_amtSum of one side of the entry.doc_numberDocument number shown on the…private_noteInternal memo entered on the…currency_idCurrency code of the document…

S04 · Step 4

Step 4: Keep the QuickBooks tables linked

Company info, accounts and journal entries stay separate tables that share realm_id as the company key; a journal line reaches its account through AccountRef. Together they become the adjustments part of one QuickBooks data model.

  • Entries and accounts both carry the company id
  • Account references inside the lines join to Accounts.id
Company inforealm_idcompany_name
Accountsidrealm_idaccount_type
Journal entriesrealm_idtxn_datetotal_amt

S05 · Step 5

Step 5: Schedule the QuickBooks refresh and backfill history

Set it once. A daily scheduled refresh keeps the tables current, and a manual backfill loads earlier periods.

  • Daily runs with no pipeline to maintain
  • Backfill entries for the periods under review
ScheduleRun on a scheduleDaily 09:00
BackfillRun backfill
Run HistoryDaily scheduleManual backfillDaily schedule

S06 · Step 6

Step 6: Reuse the same QuickBooks table everywhere

One table feeds your data model, spreadsheets, dashboards, AI assistants and scheduled insights in Slack or email.

  • Define an adjustment once
  • Every report reads the same table
QuickBooksData MartPublished
Your data model
Google Sheets
Data Studio dashboards
Claude, ChatGPT
Slack, email

Recent updates

Why OWOX

Why OWOX for QuickBooks in Databricks

Journal entries rarely reach analytics. OWOX loads them into your own Databricks workspace beside everything else you model.

  • You own the data. It lands in your own data warehouse, in tables you control.
  • Adjustments you can audit. Every entry is a row with its date, amount and note.
  • Notebook-ready. Tables in Databricks are ready for the models your data team already runs.
  • One place to fix. When QuickBooks's API changes, you publish one new connector version.

Book a callGet started free

Trust

The Data Partner You Can Trust

users

176K Source: Internal OWOX data as of 2026-10-02

Executives and data analysts across 20+ industries

G2 rating

4.9★2

“A trusted data analytics partner” — verified review

npm installs

165K3

In Open Source We Trust

Customers