Amazon SES
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. |
Communications / Data warehouse · Two-way sync platform
Amazon SES and Google Cloud Platform integration
Plan how Amazon SES and Google Cloud Platform should share data across your business. Work with Stacksync engineers on record mapping, system access, and the requirements for running the integration.
- Scope your workflow with an integration engineer
- Review the systems, records, and updates you need
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Proposed workflow
Message or conversation reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting eventA change involving Amazon SES Messages (SendEmail / SendBulkEmail) or the proposed message or conversation table in Google Cloud Platform needs a defined result in the other system.
Start with Amazon SES Messages (SendEmail / SendBulkEmail) and the proposed message or conversation table in Google Cloud Platform. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve conversation, participant, and customer context before associating messages.
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 a delivery-state change, repeated message, private conversation, and reply linked to the correct thread.
Review records and field ownershipProposed record relationships
Records to connect
Use these examples to define record matching and field ownership for your technical review.
Download the mapping worksheetCSV · No email required
| Amazon SES record | Google Cloud Platform record | Record matching | Field ownership |
|---|---|---|---|
| Messages (SendEmail / SendBulkEmail)Proposed record; confirm Stacksync object support.Reporting dataset | Proposed message or conversation tableProposed table; choose its name and schema. | Retain message ID, conversation/thread ID, channel, and sender identity. | Separate message history from actions that send new messages; preserve private/public visibility and channel consent. |
| ContactsProposed record; confirm Stacksync object support.Reporting dataset | Proposed contact tableProposed table; choose its name and schema. | Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key. | Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone. |
| Sending EventsProposed record; confirm Stacksync object support.Reporting dataset | Proposed event or activity tableProposed table; choose its name and schema. | Keep the source event ID, source system, occurrence time, and ingestion time. Use an explicit duplicate-detection key. | Decide whether the destination stores an immutable history or only a current-state summary. |
These relationships do not establish connector availability. Review the required connection and record operations with Stacksync.
Record coverage to review
Use documented coverage where available. Catalog record types are starting points for review and do not confirm Stacksync support.
Google Cloud Platform
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. |
Connection essentials
Confirm Stacksync support and account requirements for undocumented connections. Interface information alone does not establish connector availability.
View setup requirements and limits| Connection requirement | Amazon SES | Google Cloud Platform |
|---|---|---|
| Integration interface | AWS SES API v2 (REST/JSON over HTTPS) plus an SMTP sending interface | Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols |
| Authentication | Confirm the credentials, API plan, and permissions required for Amazon SES. | Confirm the credentials, API plan, and permissions required for Google Cloud Platform. |
| Change detection | Confirm how Stacksync detects changes for this connector and the objects you need. | Confirm how Stacksync detects changes for this connector and the objects you need. |
| Read access | Confirm with Stacksync | Confirm with Stacksync |
| Write access | Confirm with Stacksync | Confirm with Stacksync |
Enterprise controls
Security and control for your integrations
Explore security controlsCompliance and data transfers
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.
- SOC 2 Type II
- ISO 27001
- HIPAA BAA
- GDPR
- CCPA
- DPF US-EU-UK-CH
SSO & SCIM
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Alerts
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Secure connection options
Securely connects to your systems with:
Record-level recovery
Inspect sync errors and use retry and revert controls to resolve failed updates.
Read the recovery guideImplementation
Technical reference
Review setup, record relationships, testing, and recovery for your implementation.
Authentication, permissions and API limits
Connection requirements and limits
Amazon SES
- Integration interface
- AWS SES API v2 (REST/JSON over HTTPS) plus an SMTP sending interface
- Authentication
- Confirm the credentials, API plan, and permissions required for Amazon SES.
- Change detection
- Confirm how Stacksync detects changes for this connector and the objects you need.
- Read access
- Confirm with Stacksync
- Write access
- Confirm with Stacksync
Setup requirements
- Identify the Amazon SES account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Amazon SES, including read/write support, authentication, and initial-load limits.
Limitations to check
- Confirm Stacksync support for Amazon SES and the record types your workflow needs.
- Review write-back, deletion handling, update timing, and account limits with the integration team.
Google Cloud Platform
- Integration interface
- Per-service REST and gRPC APIs; BigQuery speaks SQL and Cloud SQL exposes standard database wire protocols
- Authentication
- Confirm the credentials, API plan, and permissions required for Google Cloud Platform.
- Change detection
- Confirm how Stacksync detects changes for this connector and the objects you need.
- Read access
- Confirm with Stacksync
- Write access
- Confirm with Stacksync
Setup requirements
- Identify the Google Cloud Platform account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Google Cloud Platform, including read/write support, authentication, and initial-load limits.
Limitations to check
- Confirm Stacksync support for Google Cloud Platform and the record types your workflow needs.
- Review write-back, deletion handling, update timing, and account limits with the integration team.
Prepare Amazon SES and Google Cloud Platform access
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.
Amazon SES setup checklist
- Identify the Amazon SES account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Amazon SES, including read/write support, authentication, and initial-load limits.
Google Cloud Platform setup checklist
- Identify the Google Cloud Platform account, edition, environment, and business objects the integration must access.
- Confirm a Stacksync connector or implementation path for Google Cloud Platform, including read/write support, authentication, and initial-load limits.
Prepare to go live
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 Amazon SES and Google Cloud Platform planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.
Record identity and field ownership
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
Messages (SendEmail / SendBulkEmail) / Proposed message or conversation table in Google Cloud Platform (choose its name)
Plan a message or conversation dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
- Amazon SES
- Object support to establish
- Google Cloud Platform
- Your database schema
- Record identity
- Retain message ID, conversation/thread ID, channel, and sender identity.
- Field ownership
- Separate message history from actions that send new messages; preserve private/public visibility and channel consent.
Fields to include
- Source message ID
- Thread reference
- Delivery state
- Timestamp
- Related record ID
- Record dependencies
- Resolve conversation, participant, and customer context before associating messages.
- Validation
- Test a delivery-state change, repeated message, private conversation, and reply linked to the correct thread.
- Recovery
- Check provider delivery state before retrying a send; replaying history must not send the message again.
Reporting dataset
Contacts / Proposed contact table in Google Cloud Platform (choose its name)
Plan a contact dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
- Amazon SES
- Object support to establish
- Google Cloud Platform
- Your database schema
- Record identity
- Use a stable person/contact ID and an explicit cross-system lookup. Email can change and can be shared, so treat it as a matching clue rather than a universal key.
- Field ownership
- Keep consent and communication preferences under an agreed authority; a general contact update must not silently resubscribe someone.
Fields to include
- Source person ID
- Display name
- Email address
- Organization reference
- Consent state
- Record dependencies
- Resolve the organization relationship and any owner or consent references required by the destination.
- Validation
- Test an email change, two records sharing an email, and a person associated with multiple organizations.
- Recovery
- Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Reporting dataset
Sending Events / Proposed event or activity table in Google Cloud Platform (choose its name)
Plan a event or activity dataset while preserving its source meaning.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
- Amazon SES
- Object support to establish
- Google Cloud Platform
- Your database schema
- Record identity
- Keep the source event ID, source system, occurrence time, and ingestion time. Use an explicit duplicate-detection key.
- Field ownership
- Decide whether the destination stores an immutable history or only a current-state summary.
Fields to include
- Source event ID
- Event type
- Occurred-at time
- Related record ID
- Payload version
- Record dependencies
- Resolve the related customer, user, or transaction identity without assuming the event ID is the entity ID.
- Validation
- Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.
- Recovery
- Identify side effects already completed before replaying an event; use the agreed deduplication key.
Compare integration approaches
Choose a method around one example record and the update your business needs. Use Messages (SendEmail / SendBulkEmail) / Proposed message or conversation table in Google Cloud Platform (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.
Stacksync managed sync
- Best fit
- Review compatibility with a Stacksync engineer using an example of the records and updates you need.
- Operating responsibility
- Fits ongoing record synchronization when the required operations are supported. Add workflow steps for approvals or business actions that go beyond copying fields.
- Before you choose
- Check record matching: Retain message ID, conversation/thread ID, channel, and sender identity. Verify field coverage, deletion handling, and how changes are detected.
Native vendor integration
- Best fit
- A vendor-built integration may fit if it supports your Amazon SES and Google Cloud Platform record types.
- Operating responsibility
- Can reduce setup for a supported workflow. You may need another method for records or business steps it does not cover.
- Before you choose
- First check whether either vendor offers this integration. If available, verify Messages (SendEmail / SendBulkEmail) / Proposed message or conversation table in Google Cloud Platform (choose its name), update direction, account tier, and related-record handling.
Custom API or workflow
- Best fit
- Consider when Amazon SES and Google Cloud Platform need a transformation, approval, or action outside a direct record sync.
- Operating responsibility
- Provides control over business steps; the team owns credentials, version changes, error queues, and reconciliation.
- Before you choose
- Verify endpoint permissions, pagination, quotas, duplicate detection, and failure recovery. Separate reading history from actions that send messages, grant access, or post transactions.
File or scheduled snapshot
- Best fit
- Consider for a one-time Amazon SES / Google Cloud Platform migration or a reporting need with an explicit freshness window.
- Operating responsibility
- Can simplify a bounded transfer; later changes and deletion history require another extraction or a separately designed incremental process.
- Before you choose
- Record the extraction cutoff, source IDs, encoding, date/number formats, and reconciliation totals.
Workflow scenarios and expected results
Message or conversation reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Messages (SendEmail / SendBulkEmail) or Proposed message or conversation table in Google Cloud Platform (choose its name) record needs a defined result in the other system.
- Start with Amazon SES Messages (SendEmail / SendBulkEmail) and Google Cloud Platform Proposed message or conversation table in Google Cloud Platform (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve conversation, participant, and customer context before associating messages.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Test a delivery-state change, repeated message, private conversation, and reply linked to the correct thread.
If it fails: Check provider delivery state before retrying a send; replaying history must not send the message again.
Contact reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Contacts or Proposed contact table in Google Cloud Platform (choose its name) record needs a defined result in the other system.
- Start with Amazon SES Contacts and Google Cloud Platform Proposed contact table in Google Cloud Platform (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve the organization relationship and any owner or consent references required by the destination.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Test an email change, two records sharing an email, and a person associated with multiple organizations.
If it fails: Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Event or activity reporting workflow
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Sending Events or Proposed event or activity table in Google Cloud Platform (choose its name) record needs a defined result in the other system.
- Start with Amazon SES Sending Events and Google Cloud Platform Proposed event or activity table in Google Cloud Platform (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
- Resolve the related customer, user, or transaction identity without assuming the event ID is the entity ID.
- Test a normal update and one failed or repeated update in the supported direction. Keep both record IDs with the test results.
Expected result: Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.
If it fails: Identify side effects already completed before replaying an event; use the agreed deduplication key.
Link communication history with Google Cloud Platform context
This is an evaluation scenario; connector and operation support require confirmation.
Starting event: A communication in Amazon SES needs an association with Firestore documents in Google Cloud Platform.
- Select the communication records from Messages (SendEmail / SendBulkEmail) or Contacts and preserve message/call and thread IDs.
- Resolve the participant-to-business-record relationship explicitly; phone number or display name alone may be ambiguous.
- Keep history replication separate from sending a message, placing a call, or changing consent. Confirm a separate authorized operation for any action.
Expected result: Repeated delivery updates the same history record; a private conversation stays private; a history replay sends no new message.
If it fails: Check source delivery state and the destination relationship before retrying. Do not resend to repair an analytical or history discrepancy.
Initial load and acceptance testing
Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.
Messages (SendEmail / SendBulkEmail) / Proposed message or conversation table in Google Cloud Platform (choose its name)
Test case
Test a delivery-state change, repeated message, private conversation, and reply linked to the correct thread.
Expected result
The expected message or conversation relationship is preserved with no duplicate action or unintended write.
Contacts / Proposed contact table in Google Cloud Platform (choose its name)
Test case
Test an email change, two records sharing an email, and a person associated with multiple organizations.
Expected result
The expected contact relationship is preserved with no duplicate action or unintended write.
Sending Events / Proposed event or activity table in Google Cloud Platform (choose its name)
Test case
Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.
Expected result
The expected event or activity relationship is preserved with no duplicate action or unintended write.
Direction and permissions
Test case
Bring an example source record and the intended destination operation to the compatibility review. Confirm the supported route before granting write access.
Expected result
Only an approved, supported direction and permitted fields are written.
Freshness and reconciliation
Test case
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.
Expected result
The process meets its agreed freshness target and reconciliation has no unexplained differences.
Failed updates, retries and recovery
Start with the failed record and the destination error, then inspect the source value, field requirements, and access.
Rejected or repeated message or conversation change
Investigate
Inspect Amazon SES Messages (SendEmail / SendBulkEmail) and Google Cloud Platform Proposed message or conversation table in Google Cloud Platform (choose its name), their IDs, and the destination error.
Next action
Check provider delivery state before retrying a send; replaying history must not send the message again.
Rejected or repeated contact change
Investigate
Inspect Amazon SES Contacts and Google Cloud Platform Proposed contact table in Google Cloud Platform (choose its name), their IDs, and the destination error.
Next action
Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Rejected or repeated event or activity change
Investigate
Inspect Amazon SES Sending Events and Google Cloud Platform Proposed event or activity table in Google Cloud Platform (choose its name), their IDs, and the destination error.
Next action
Identify side effects already completed before replaying an event; use the agreed deduplication key.
A record type or update is unavailable
Investigate
Check the Amazon SES and Google Cloud Platform connector guides, account permissions, and any operations marked On Request.
Next action
Ask the integration team to confirm a supported way to handle that record. Verify whether it needs connector configuration or a separate workflow step.
Source and destination disagree after a retry
Investigate
Compare current source values, destination validation, identity mappings, and any side effects already completed.
Next action
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.
Change detection and update delivery
How updates move between Amazon SES and Google Cloud Platform
See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.
Amazon SES Google Cloud Platform Direction requires confirmation
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 Google Cloud Platform.
Google Cloud Platform Amazon SES Direction requires confirmation
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 Amazon SES.
Update timing and record limits
- Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
- Review write-back, deletion handling, update timing, and account limits with the integration team.
- Review write-back, deletion handling, update timing, and account limits with the integration team.
FAQ
Amazon SES and Google Cloud Platform integration FAQ
-
Explore a Amazon SES and Google Cloud Platform integration with a Stacksync engineer. Stacksync support for Amazon SES and Google Cloud Platform 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.
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Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Identify the Amazon SES account, edition, environment, and business objects the integration must access. Identify the Google Cloud Platform account, edition, environment, and business objects the integration must access. Use the pair worksheet to record ownership and acceptance criteria.
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Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.
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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.
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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.
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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.
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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.
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Start by reviewing Messages (SendEmail / SendBulkEmail) in Amazon SES and Proposed message or conversation table in Google Cloud Platform (choose its name) in Google Cloud Platform. 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 Messages (SendEmail / SendBulkEmail) / Proposed message or conversation table in Google Cloud Platform (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.
Integration directory
Related integrations
Review documented support, sync direction, and setup requirements on each pair page. Search all 443 integrations listed for Amazon SES and Google Cloud Platform.
Next step
Plan your integration with an engineer
Walk through your Amazon SES and Google Cloud Platform records, field mappings, and requirements with an integration engineer.
