Can you integrate Aircall with BigQuery?

Explore a Aircall and BigQuery integration with a Stacksync engineer. Stacksync support for Aircall 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.

Can Aircall and BigQuery sync in both directions?

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.

What should be ready before the Aircall and BigQuery initial load?

Prepare both accounts, the selected object schemas, stable source and destination IDs, and the expected outcome. Identify the Aircall account, edition, environment, and business objects the integration must access. Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project. Use the pair worksheet to record ownership and acceptance criteria.

How fast does the Aircall to BigQuery sync run?

Measure initial-load and ongoing-change latency separately. Source detection, selected objects, account limits, and destination validation determine the observed delay.

Will existing duplicates merge automatically?

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.

How do I map Aircall fields to BigQuery?

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.

What should I do if a record fails to sync?

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.

What does a Aircall and BigQuery integration cost?

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.

Which records should the Aircall and BigQuery pilot start with?

Start by reviewing Calls in Aircall and Proposed call history record table in BigQuery (choose its name) in BigQuery. 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.

Communications / Data warehouse · Two-way sync platform

Aircall and BigQuery integration

Plan how Aircall and BigQuery 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

Integration planning

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Aircall

BigQuery

Review the integration scope

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Proposed workflow

Call history record reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting eventA change involving Aircall Calls or the proposed call history record table in BigQuery needs a defined result in the other system.

Start with Aircall Calls and the proposed call history record table in BigQuery. Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve participant and business-record identities, provider/account scope, and any related recording access.
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 two calls to the same number, a corrected disposition, and a delayed call completion. Verify that the intended CRM activity is updated once.

Review records and field ownership

Proposed record relationships

Records to connect

Use these examples to define record matching and field ownership for your technical review.

Download the mapping worksheet

CSV · No email required

Example record relationships between Aircall and BigQuery
Aircall record	BigQuery record	Record matching	Field ownership
CallsProposed record; confirm Stacksync object support.Reporting dataset	Proposed call history record tableProposed table; choose its name and schema.	Retain the source call ID, provider/account context, and the explicit relationship to a CRM activity. A phone number alone cannot identify one call.	Keep call history and disposition separate from actions that place a call or change routing; assign an owner for corrected activity details.
Messages (SMS/MMS)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.

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.

Aircall

Connection and object support require review

Record types to review with Stacksync

Record types	Coverage and requirements
Contacts Calls Users Numbers Tags Teams	Confirm support for this record type and the direction you need.

Discuss Aircall requirements

BigQuery

Read and write support varies by record

Record types covered in the setup guide

Record types	Coverage and requirements
Tables	See connector requirements. Confirm field permissions and sync direction.

Read the BigQuery connector guide

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	Aircall	BigQuery
Integration interface	REST API (Aircall Public API v1, https://api.aircall.io/v1)	GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication	Confirm the credentials, API plan, and permissions required for Aircall.	Dedicated Google Cloud service account and JSON key
Change detection	Confirm how Stacksync detects changes for this connector and the objects you need.	The setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project.
Read access	Confirm with Stacksync	Available for supported records
Write access	Confirm with Stacksync	Available for supported records

Enterprise controls

Security and control for your integrations

Explore security controls

Compliance 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.

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ISO 27001
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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 guide

Implementation

Technical reference

Review setup, record relationships, testing, and recovery for your implementation.

Authentication, permissions and API limits

Connection requirements and limits

Aircall

Integration interface: REST API (Aircall Public API v1, https://api.aircall.io/v1)
Authentication: Confirm the credentials, API plan, and permissions required for Aircall.
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 Aircall account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Aircall, including read/write support, authentication, and initial-load limits.

Limitations to check

Confirm Stacksync support for Aircall and the record types your workflow needs.
Review write-back, deletion handling, update timing, and account limits with the integration team.

Technical documentation

Aircall vendor API documentation

BigQuery

Integration interface: GoogleSQL via the BigQuery REST API, client libraries, JDBC/ODBC drivers, and the Storage Read/Write APIs
Authentication: Dedicated Google Cloud service account and JSON key; enable the APIs and grant the roles in the authorization guide.
Change detection: The setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project.
Read access: Available for supported records
Write access: Available for supported records

Setup requirements

Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project.
Create a dedicated service account with the roles in the authorization guide and supply its credentials through Stacksync.

Limitations to check

Only tables are supported in the saved guide; ordinary and materialized views are excluded.
Google Cloud quotas and the selected write method affect capacity; validate the current project limits before a large backfill.

Technical documentation

Documentation reviewed 2026-09-15. Check the linked guides for current account and record requirements.

BigQuery setup guide

Prepare Aircall and BigQuery 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.

Aircall setup checklist

Identify the Aircall account, edition, environment, and business objects the integration must access.
Confirm a Stacksync connector or implementation path for Aircall, including read/write support, authentication, and initial-load limits.

BigQuery setup checklist

Enable BigQuery, Cloud Run, Cloud Resource Manager, and Eventarc APIs in the target project.
Create a dedicated service account with the roles in the authorization guide and supply its credentials through Stacksync.

Setup guides: Authorize BigQuery

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 Aircall and BigQuery planning worksheet to capture these decisions. Record the access owner in the worksheet and enter credentials only in the connection setup.

Talk to an engineer · Review current pricing

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

Calls / Proposed call history record table in BigQuery (choose its name)

Plan a call history record dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Aircall: Object support to establish
BigQuery: Your database schema
Record identity: Retain the source call ID, provider/account context, and the explicit relationship to a CRM activity. A phone number alone cannot identify one call.
Field ownership: Keep call history and disposition separate from actions that place a call or change routing; assign an owner for corrected activity details.

Fields to include

Source call ID
Participant reference
Start time
Duration
Disposition or outcome

Record dependencies: Resolve participant and business-record identities, provider/account scope, and any related recording access.
Validation: Test two calls to the same number, a corrected disposition, and a delayed call completion. Verify that the intended CRM activity is updated once.
Recovery: Look up the current call and destination activity before retrying; repairing history must not place another call or expose a restricted recording.

References: Aircall: Calls documentation

Reporting dataset

Messages (SMS/MMS) / Proposed message or conversation table in BigQuery (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.

Aircall: Object support to establish
BigQuery: 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.

References: Aircall: Messages (SMS/MMS) documentation

Reporting dataset

Contacts / Proposed contact table in BigQuery (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.

Aircall: Object support to establish
BigQuery: 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.

References: Aircall: Contacts documentation

Reporting dataset

Users / Proposed application user or identity table in BigQuery (choose its name)

Plan a application user or identity dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Aircall: Object support to establish
BigQuery: Your database schema
Record identity: Use the immutable user ID within the tenant or directory. Do not equate an application user with a CRM customer contact.
Field ownership: Identity and application owners approve account lifecycle and access changes; synchronize only approved attributes.

Fields to include

Source user ID
Tenant reference
Account status
Group references

Record dependencies: Resolve tenant and group references and establish a protected administrative-account policy.
Validation: Test a renamed login, disabled account, missing group, and a user existing in two tenants.
Recovery: Review access impact before retrying a lifecycle change; reconcile current identity state and retain an approval trail.

References: Aircall: Users documentation

Reporting dataset

Teams / Proposed group or membership table in BigQuery (choose its name)

Plan a group or membership dataset while preserving its source meaning.

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Aircall: Object support to establish
BigQuery: Your database schema
Record identity: Keep group IDs and membership relationships separately from group names.
Field ownership: The access owner controls membership; reporting a group is different from granting its permissions.

Fields to include

Source group ID
Member references
Tenant reference
Group type

Record dependencies: Resolve user and tenant identities before membership changes.
Validation: Test removed membership, nested groups, and equal group names in different tenants.
Recovery: Recompute the approved membership delta before retrying; do not replay an outdated access grant.

References: Aircall: Teams documentation

Compare integration approaches

Choose a method around one example record and the update your business needs. Use Calls / Proposed call history record table in BigQuery (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 the source call ID, provider/account context, and the explicit relationship to a CRM activity. A phone number alone cannot identify one call. 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 Aircall and BigQuery 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 Calls / Proposed call history record table in BigQuery (choose its name), update direction, account tier, and related-record handling.

Custom API or workflow

Best fit: Consider when Aircall and BigQuery 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 Aircall / BigQuery 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

Call history record reporting workflow

Planning example. Stacksync support for the required connection and record operations needs a technical review.

Starting event: A change to the selected Calls or Proposed call history record table in BigQuery (choose its name) record needs a defined result in the other system.

Start with Aircall Calls and BigQuery Proposed call history record table in BigQuery (choose its name). Use the record-matching and field-ownership rules from your mapping worksheet.
Resolve participant and business-record identities, provider/account scope, and any related recording access.
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 two calls to the same number, a corrected disposition, and a delayed call completion. Verify that the intended CRM activity is updated once.

If it fails: Look up the current call and destination activity before retrying; repairing history must not place another call or expose a restricted recording.

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 (SMS/MMS) or Proposed message or conversation table in BigQuery (choose its name) record needs a defined result in the other system.

Start with Aircall Messages (SMS/MMS) and BigQuery Proposed message or conversation table in BigQuery (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 BigQuery (choose its name) record needs a defined result in the other system.

Start with Aircall Contacts and BigQuery Proposed contact table in BigQuery (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.

Link communication history with BigQuery context

This is an evaluation scenario; connector and operation support require confirmation.

Starting event: A communication in Aircall needs an association with a selected destination dataset in BigQuery.

Select the communication records from Contacts or Calls 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.

Calls / Proposed call history record table in BigQuery (choose its name)

Test case

Test two calls to the same number, a corrected disposition, and a delayed call completion. Verify that the intended CRM activity is updated once.

Expected result

The expected call history record relationship is preserved with no duplicate action or unintended write.

Messages (SMS/MMS) / Proposed message or conversation table in BigQuery (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 BigQuery (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.

Users / Proposed application user or identity table in BigQuery (choose its name)

Test case

Test a renamed login, disabled account, missing group, and a user existing in two tenants.

Expected result

The expected application user or identity 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 call history record change

Investigate

Inspect Aircall Calls and BigQuery Proposed call history record table in BigQuery (choose its name), their IDs, and the destination error.

Next action

Look up the current call and destination activity before retrying; repairing history must not place another call or expose a restricted recording.

Rejected or repeated message or conversation change

Investigate

Inspect Aircall Messages (SMS/MMS) and BigQuery Proposed message or conversation table in BigQuery (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 Aircall Contacts and BigQuery Proposed contact table in BigQuery (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.

A record type or update is unavailable

Investigate

Check the Aircall and BigQuery 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 Aircall and BigQuery

See how each system detects changes and which updates the other system can receive. Each direction has its own permissions and record requirements.

Aircall BigQuery 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 BigQuery.

BigQuery Aircall Direction requires confirmation

Detect changesThe setup provisions notification services using Eventarc and Cloud Run in the customer Google Cloud project.

Apply updatesConfirm that Stacksync can create or update the records you need in Aircall.

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.
Google Cloud quotas and the selected write method affect capacity; validate the current project limits before a large backfill.

FAQ