Azure Cosmos DB
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 Azure Cosmos DB and Firebase 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 Azure Cosmos DB Items (JSON documents) or Firebase Firestore Documents needs a defined result in the other system.
Start with Azure Cosmos DB Items (JSON documents) and Firebase Firestore Documents. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve folder/container and parent-record references before attaching metadata.
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 renamed file, a new version, a moved folder, and an access-restricted document.
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
| Azure Cosmos DB record | Firebase record | Record matching | Field ownership |
|---|---|---|---|
| Items (JSON documents)Proposed record; confirm Stacksync object support.Record matching | Firestore DocumentsProposed record; confirm Stacksync object support. | Keep file/object ID, container, and version. A path can change and a filename can repeat. | Separate document content, metadata, and sharing permissions; a metadata sync does not imply file transfer or ACL replication. |
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 | Azure Cosmos DB | Firebase |
|---|---|---|
| Integration interface | REST API and SDKs over HTTPS (API for NoSQL, formerly the SQL API); also MongoDB, Cassandra, Gremlin, and Table API surfaces | REST and gRPC APIs, typically accessed through the Firebase Admin SDK |
| Authentication | Confirm the credentials, API plan, and permissions required for Azure Cosmos DB. | Confirm the credentials, API plan, and permissions required for Firebase. |
| 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 Azure Cosmos DB and Firebase 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
Record matching
Compare whether Azure Cosmos DB Items (JSON documents) and Firebase Firestore Documents describe the same file or document metadata in your business.
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 Items (JSON documents) / Firestore Documents 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 Items (JSON documents) or Firestore Documents record needs a defined result in the other system.
Expected result: Test a renamed file, a new version, a moved folder, and an access-restricted document.
If it fails: Check the current file version and destination access before retrying transfer or metadata updates.
This is an evaluation scenario; connector and operation support require confirmation.
Starting event: A selected source table needs an operational replica, a reporting projection, or a migration copy.
Expected result: Counts reconcile within identical filters; updates preserve keys; precision, nulls, deletes, and schema changes follow the agreed mapping rules.
If it fails: Compare current source state, key mapping, and destination constraints before retrying. Reconcile the backlog after any schema or permission change.
Keep both record IDs with the expected and actual result. Reconcile the same filters and time window in each system.
Test a renamed file, a new version, a moved folder, and an access-restricted document.
The expected file or document metadata 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.
Use an actual Azure Cosmos DB and Firebase table. Compare key uniqueness, nulls, decimal precision, timezone conversions, and counts within identical filters.
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 Azure Cosmos DB Items (JSON documents) and Firebase Firestore Documents, their IDs, and the destination error.
Check the current file version and destination access before retrying transfer or metadata updates.
Check the Azure Cosmos DB and Firebase 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 Firebase.
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 Azure Cosmos DB.
Explore a Azure Cosmos DB and Firebase integration with a Stacksync engineer. Stacksync support for Azure Cosmos DB and Firebase 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 Azure Cosmos DB account, edition, environment, and business objects the integration must access. Identify the Firebase 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 Items (JSON documents) in Azure Cosmos DB and Firestore Documents in Firebase. 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 Items (JSON documents) / Firestore Documents 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 Azure Cosmos DB and Firebase records, field mappings, and requirements with an integration engineer.