Eloqua
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 Eloqua and Neo4j 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 Eloqua Contacts or the proposed contact table in Neo4j needs a defined result in the other system.
Start with Eloqua Contacts and the proposed contact table in Neo4j. 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.
What to verifyTest an email change, two records sharing an email, and a person associated with multiple organizations.
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
| Eloqua record | Neo4j record | Record matching | Field ownership |
|---|---|---|---|
| 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. |
| CampaignsProposed record; confirm Stacksync object support.Reporting dataset | Proposed campaign or audience tableProposed table; choose its name and schema. | Keep campaign ID, channel/account context, and separate audience membership IDs. | Marketing owns campaign activation and audience eligibility; analytical metrics do not imply permission to launch a campaign. |
| AccountsProposed record; confirm Stacksync object support.Reporting dataset | Proposed company tableProposed table; choose its name and schema. | Retain the source company ID and the destination customer/company ID. Separate legal entities, subsidiaries, and business units; a shared name or web domain is insufficient. | Assign ownership separately for relationship details and finance-controlled billing details. |
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. |
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. |
Confirm Stacksync support and account requirements for undocumented connections. Interface information alone does not establish connector availability.
View setup requirements and limits| Connection requirement | Eloqua | Neo4j |
|---|---|---|
| Integration interface | Bulk API 2.0 (contacts, accounts, custom data objects, activities) plus Application REST API (campaigns, emails, forms, lists) | Bolt binary protocol with Cypher via official drivers, plus an HTTP query API |
| Authentication | Confirm the credentials, API plan, and permissions required for Eloqua. | Confirm the credentials, API plan, and permissions required for Neo4j. |
| 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
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.
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.
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 Eloqua and Neo4j 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 contact 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 campaign or audience 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 company 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 event or activity 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 Contacts / Proposed contact table in Neo4j (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 Contacts or Proposed contact table in Neo4j (choose its name) record needs a defined result in the other system.
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.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Campaigns or Proposed campaign or audience table in Neo4j (choose its name) record needs a defined result in the other system.
Expected result: Test a removed audience member, a paused campaign, and one campaign reported across multiple channels.
If it fails: Rebuild the current eligible audience before retrying activation or membership updates.
Planning example. Stacksync support for the required connection and record operations needs a technical review.
Starting event: A change to the selected Accounts or Proposed company table in Neo4j (choose its name) record needs a defined result in the other system.
Expected result: Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
If it fails: Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.
This is an evaluation scenario; connector and operation support require confirmation.
Starting event: An approved customer or campaign change affects eligibility or reporting in Eloqua.
Expected result: A removed or ineligible person stays excluded after a repeated update; audience membership refers to the correct identity.
If it fails: Recompute current eligibility before retrying membership or activation; do not replay an obsolete permission to contact someone.
Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.
Test an email change, two records sharing an email, and a person associated with multiple organizations.
The expected contact relationship is preserved with no duplicate action or unintended write.
Test a removed audience member, a paused campaign, and one campaign reported across multiple channels.
The expected campaign or audience relationship is preserved with no duplicate action or unintended write.
Use two organizations with similar names and one with multiple business units. Verify that an update reaches the intended entity only.
The expected company relationship is preserved with no duplicate action or unintended write.
Deliver the same event twice, then an older event after a newer one; verify duplicate and ordering behavior.
The expected event or activity 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 Eloqua Contacts and Neo4j Proposed contact table in Neo4j (choose its name), their IDs, and the destination error.
Hold ambiguous matches for review and reconcile the person ID before retrying; preserve the consent decision already recorded by its owner.
Inspect Eloqua Campaigns and Neo4j Proposed campaign or audience table in Neo4j (choose its name), their IDs, and the destination error.
Rebuild the current eligible audience before retrying activation or membership updates.
Inspect Eloqua Accounts and Neo4j Proposed company table in Neo4j (choose its name), their IDs, and the destination error.
Repair the cross-system ID relationship before retrying dependent records; do not merge companies solely to remove a sync error.
Check the Eloqua and Neo4j 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 Neo4j.
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 Eloqua.
Explore a Eloqua and Neo4j integration with a Stacksync engineer. Stacksync support for Eloqua and Neo4j 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 Eloqua account, edition, environment, and business objects the integration must access. Identify the Neo4j account, edition, environment, and business objects the integration must access. 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 Contacts in Eloqua and Proposed contact table in Neo4j (choose its name) in Neo4j. 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 Contacts / Proposed contact table in Neo4j (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 Eloqua and Neo4j records, field mappings, and requirements with an integration engineer.