SAP
Connection and object support require review
Record types to review with Stacksync
| Record types | Coverage and requirements |
|---|---|
| Confirm support for this record type and the direction you need. |
Plan how SAP and Snowflake should share data across your business. Work with Stacksync engineers on record mapping, system access, and the requirements for running the integration.
Proposed workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting eventA change involving SAP Business Partners or the proposed customer table in Snowflake needs a defined result in the other system.
Start with SAP Business Partners and the proposed customer table in Snowflake. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve person or company type, legal entity, business role, and any billing account before transactions.
Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
What to verifyTest an individual buyer, a company buyer, and one company with multiple billing relationships. Do not merge these into a single generic contact.
Review records and field ownershipProposed record relationships
Use these examples to define record matching and field ownership for your technical review.
Download the mapping worksheetCSV · No email required
| SAP record | Snowflake record | Record matching | Field ownership |
|---|---|---|---|
| Business PartnersProposed record; confirm Stacksync object support.Reporting dataset | Proposed customer tableProposed table; choose its name and schema. | Determine whether each customer represents an individual, a company, or a business-unit relationship before matching it to a contact or organization. Retain the source customer ID and destination ID; names and email alone are insufficient. | Separate the customer relationship from contact details, billing authority, and consent. Choose an owner for each field after identifying whether the customer is a person or company. |
| Sales OrdersProposed record; confirm Stacksync object support.Reporting dataset | Proposed sales order tableProposed table; choose its name and schema. | Preserve both the order ID and stable line IDs. Allow one order to relate to several shipments or invoices. | Decide which system approves the order and which can cancel or amend it after fulfillment begins. |
| GL Accounts and Journal EntriesProposed record; confirm Stacksync object support.Reporting dataset | Proposed journal or ledger entry tableProposed table; choose its name and schema. | Retain journal ID and line IDs within the legal entity and accounting period. | The ledger owns posting approval and period controls; an integration should not treat a posted journal as an ordinary editable row. |
These relationships do not establish connector availability. Review the required connection and record operations with Stacksync.
Use documented coverage where available. Catalog record types are starting points for review and do not confirm Stacksync support.
Connection and object support require review
Record types to review with Stacksync
| Record types | Coverage and requirements |
|---|---|
| Confirm support for this record type and the direction you need. |
Read and write support varies by record
Record types covered in the setup guide
| Record types | Coverage and requirements |
|---|---|
| ✅ Supported. Confirm field permissions and sync direction. |
| 🕘 Coming soon. Confirm field permissions and sync direction. |
| ❌ Not supported. Confirm field permissions and sync direction. |
Confirm Stacksync support and account requirements for undocumented connections. Interface information alone does not establish connector availability.
View setup requirements and limits| Connection requirement | SAP | Snowflake |
|---|---|---|
| Integration interface | OData (v2/v4) APIs on S/4HANA; BAPI/RFC and IDoc on ECC and on-prem systems; SOAP services | SQL via JDBC/ODBC and native drivers, plus the Snowflake SQL REST API |
| Authentication | Confirm the credentials, API plan, and permissions required for SAP. | Dedicated Snowflake service user + role with RSA key-pair authentication |
| Change detection | Confirm how Stacksync detects changes for this connector and the objects you need. | The saved Stacksync guide does not specify the change-detection mechanism. |
| Read access | Confirm with Stacksync | Available for supported records |
| Write access | Confirm with Stacksync | Available for supported records |
Enterprise controls
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Inspect sync errors and use retry and revert controls to resolve failed updates.
Read the recovery guideImplementation
Review setup, record relationships, testing, and recovery for your implementation.
Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.
Set up both accounts before testing the mapping. Use test records where available, and identify the account administrator who can approve access and help resolve setup errors.
Setup guides: Authorize Snowflake
Record the fields each system can update, the first-load cutoff, both record IDs, the expected update delay, and who handles errors. Complete the tests before production before expanding to more records.
Use the SAP and Snowflake planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.
Use these data-model references to describe the records your connection needs. They are planning examples; connector availability and supported operations must be established before implementation.
Download the mapping worksheet · CSV, no email required
Reporting dataset
Plan a customer dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Reporting dataset
Plan a sales order dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Reporting dataset
Plan a journal or ledger entry dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Reporting dataset
Plan a product or catalog item dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Reporting dataset
Plan a inventory or stock position dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Reporting dataset
Plan a purchase order dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Fields to include
Choose a method around one example record and the update your business needs. Use Business Partners / Proposed customer table in Snowflake (choose its name) to review record matching and confirm Stacksync support for the required operations. Compare ongoing sync, a custom workflow, and a scheduled export against that requirement.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Business Partners or Proposed customer table in Snowflake (choose its name) record needs a defined result in the other system.
Expected result: Test an individual buyer, a company buyer, and one company with multiple billing relationships. Do not merge these into a single generic contact.
If it fails: Hold ambiguous customer matches for review and resolve customer type before retrying dependent records.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Sales Orders or Proposed sales order table in Snowflake (choose its name) record needs a defined result in the other system.
Expected result: Test a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.
If it fails: Check for an existing destination order before retrying a timed-out create; reconcile line IDs to avoid duplicate fulfillment.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected GL Accounts and Journal Entries or Proposed journal or ledger entry table in Snowflake (choose its name) record needs a defined result in the other system.
Expected result: Verify balanced debits and credits, dimension requirements, and rejection for a closed period.
If it fails: Reconcile posting status and use the finance-approved reversal or adjustment process instead of replaying a posted entry.
This is an evaluation scenario; connector and operation support require confirmation.
Starting event: A finance-owned record in SAP needs operational visibility through a selected destination dataset.
Expected result: Totals reconcile within the same entity/currency/window; a repeated handoff creates no duplicate financial transaction.
If it fails: Verify posting and settlement state before retrying. Use the approved adjustment path for already-posted transactions.
Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.
Test an individual buyer, a company buyer, and one company with multiple billing relationships. Do not merge these into a single generic contact.
The expected customer relationship is preserved with no duplicate action or unintended write.
Test a multi-line order, a partial cancellation, and two partial shipments. Compare line totals as well as the header.
The expected sales order relationship is preserved with no duplicate action or unintended write.
Verify balanced debits and credits, dimension requirements, and rejection for a closed period.
The expected journal or ledger entry relationship is preserved with no duplicate action or unintended write.
Test two variants of one product, a changed SKU, and a price that applies to only one market or currency.
The expected product or catalog item relationship is preserved with no duplicate action or unintended write.
Bring an example source record and the intended destination operation to the compatibility review. Confirm the supported route before granting write access.
Only an approved, supported direction and permitted fields are written.
Measure source and destination times for the selected records under normal load and a burst. Reconcile IDs and values using the same filters and cutoff.
The process meets its agreed freshness target and reconciliation has no unexplained differences.
Start with the failed record and the destination error, then inspect the source value, field requirements, and access.
Inspect SAP Business Partners and Snowflake Proposed customer table in Snowflake (choose its name), their IDs, and the destination error.
Hold ambiguous customer matches for review and resolve customer type before retrying dependent records.
Inspect SAP Sales Orders and Snowflake Proposed sales order table in Snowflake (choose its name), their IDs, and the destination error.
Check for an existing destination order before retrying a timed-out create; reconcile line IDs to avoid duplicate fulfillment.
Inspect SAP GL Accounts and Journal Entries and Snowflake Proposed journal or ledger entry table in Snowflake (choose its name), their IDs, and the destination error.
Reconcile posting status and use the finance-approved reversal or adjustment process instead of replaying a posted entry.
Check the SAP and Snowflake connector guides, account permissions, and any operations marked On Request.
Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.
Compare current source values, destination validation, identity mappings, and any side effects already completed.
Stacksync issue retry reads the current source state. Decide the intended state before retrying or reverting; reconcile downstream effects separately.
Read the Stacksync issues dashboard guide for retry and revert behavior.
See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.
Detect changesConfirm how Stacksync detects changes for this connector and the objects you need.
Apply updatesConfirm that Stacksync can create or update the records you need in Snowflake.
Detect changesThe saved Stacksync guide does not specify the change-detection mechanism. Confirm it for the selected objects.
Apply updatesConfirm that Stacksync can create or update the records you need in SAP.
Explore a SAP and Snowflake integration with a Stacksync engineer. Stacksync support for SAP is not established by the connector documentation reviewed for this page. Start with one record and the update your business needs to identify an implementation path.
Confirm two-way support with Stacksync for the records and fields you need in both systems. Access to a vendor API does not confirm that its Stacksync connector supports write-back.
Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Identify the SAP account, edition, environment, and business objects the integration must access. Have an administrator run the documented setup script for a dedicated service user and role with RSA key-pair authentication. Use the pair worksheet to record ownership and acceptance criteria.
Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
No. Stacksync documents that pre-existing duplicates are not merged automatically when two-way sync begins. Review the initial dataset and matching plan before enabling it; an empty destination can simplify the first load.
Start with one business entity and a stable record ID. Map a small set of editable fields with compatible types, test required values and relationships, then expand after the pilot passes.
Check the destination error, field constraints, permissions, and current source value. The Stacksync issues dashboard supports retry and revert; retry reads current source values, so verify the intended record state before acting.
Use the current Stacksync pricing page and confirm the supported implementation with the team. Scope the required objects, record volume, update frequency, initial load, and support needs when comparing a managed connector with native or custom development.
Start by reviewing Business Partners in SAP and Proposed customer table in Snowflake (choose its name) in Snowflake. Check how these records relate in your workflow, then confirm the actual fields and supported operations. Test record matching and one failed or repeated update before adding more records.
Choose a method around one example record and the update your business needs. Use Business Partners / Proposed customer table in Snowflake (choose its name) to review record matching and confirm Stacksync support for the required operations. Compare ongoing sync, a custom workflow, and a scheduled export against that requirement.
Next step
Walk through your SAP and Snowflake records, field mappings, and requirements with an integration engineer.