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Communications ⇄ Data warehouse

Aircall to Databricks integration — real-time, two-way sync

Keep Aircall and Databricks in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Aircall and Databricks

Land the messages, calls, and events from Aircall in Databricks as live tables, and write results back, without building or maintaining a pipeline.

Aircall produces a constant stream of activity — messages sent and received, calls placed and answered, meetings held, and the delivery and engagement events attached to them. That record is what the rest of the company wants to analyze, and it usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay to get it out.

Stacksync syncs Users, Numbers, Tags, Teams from Aircall into tables in Databricks in real time, handling schema, rate limits, and retries. Because the connection works in both directions, results computed in Databricks — segments, contact updates, suppression flags — can be written back into fields in Aircall wherever it exposes them, so analysis lands where outreach actually happens.

Common use cases

  • 01 Provision and deprovision Users and Team membership from an HR system or IdP so the agent roster, seats, and routing groups stay current.
  • 02 Send outbound SMS/MMS through the Messages API when a CRM or database record changes (appointment reminders, alerts) and write inbound replies back.
  • 03 Serve ML feature outputs computed in Databricks to production apps through a synced operational store.
  • 04 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.

Common sync patterns

Engagement and delivery on live data

Sends, opens, clicks, bounces, and call outcomes from Aircall land in Databricks as they happen, so deliverability and response monitoring stop lagging the reality they describe.

Activity joined with everything else

Combine Aircall's activity with the CRM, product, and support data already in Databricks to attribute outcomes to the touches that drove them, which no single tool can do alone.

Where Aircall accepts updates: operational write-back

Segments, contact fields, or suppression flags computed in Databricks sync back onto records in Aircall, putting warehouse analysis where the outreach happens.

What you can sync between Aircall and Databricks

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Aircall objects Databricks objects How this pairing syncs
Calls Inbound and outbound call records with recording URL, duration, tags, comments, and metadata; the record itself is read-only, but you can add tags, comments, insight cards, transfer, archive, and control recording. Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. Calls is specific to Aircall and Materialized Views to Databricks — each maps to any object or custom field on the other side.
Users Agent seats with name, email, and availability; full CRUD to provision or deprovision seats and map Aircall agents to CRM, HR, or directory identities. Volumes Unity Catalog file storage used for staging bulk loads. Users is specific to Aircall and Volumes to Databricks — each maps to any object or custom field on the other side.
Numbers Provisioned phone numbers with settings, open hours, and IVR config; read and update to keep routing and business-hours data aligned across systems. SQL Warehouses The compute endpoint a sync connects to for query execution. Numbers is specific to Aircall and SQL Warehouses to Databricks — each maps to any object or custom field on the other side.
Tags Call tags with name and color; full CRUD, applied to calls for disposition and outcome reporting in the CRM or warehouse. Change Data Feed Row-level change records on Delta tables that drive incremental reads. Tags is specific to Aircall and Change Data Feed to Databricks — each maps to any object or custom field on the other side.
Teams Groups of users for routing and reporting; create and delete teams and add or remove members to mirror org structure from an HR system or IdP. Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Teams is specific to Aircall and Catalogs to Databricks — each maps to any object or custom field on the other side.
Messages (SMS/MMS) Text messages tied to a number and contact; send outbound SMS/MMS through the API and read inbound messages delivered via webhook events. Schemas Group tables and views; syncs typically target a dedicated schema per source system. Messages (SMS/MMS) is specific to Aircall and Schemas to Databricks — each maps to any object or custom field on the other side.

How changes propagate between Aircall and Databricks

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Aircall Databricks Sub-second propagation

DetectionAircall notifies Stacksync of record changes through webhook events. Webhooks (POST /v1/webhooks) for call, contact, user, message, and number events.

DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.

Databricks Aircall Sub-second propagation

DetectionChanges in Databricks are captured at the source via change data capture — no polling loop against its API. Delta Lake Change Data Feed for row-level changes.

DeliveryEach detected change is written to Aircall through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Aircall: 60 requests per minute per company by default (120/min for Advanced Messaging customers); responses carry X-AircallApi-Limit, X-AircallApi-Remaining, and X-AircallApi-Reset headers.
  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Aircall ⇄ Databricks

Connect Aircall and Databricks for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Aircall–Databricks connection.

Real-time

Two-way sync

Changes in Aircall or Databricks instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Aircall or Databricks data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Aircall or Databricks record.

Observability

Monitoring

Track your Aircall ⇄ Databricks sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Aircall and Databricks.

How the Aircall and Databricks connectors work

Aircall

Integration surface
REST API (Aircall Public API v1, https://api.aircall.io/v1)
Authentication
HTTP Basic auth (base64 api_id:api_token) for single-account integrations, or OAuth 2.0 authorization_code flow for multi-tenant Technology Partner apps
Change detection
Webhooks (POST /v1/webhooks) for call, contact, user, message, and number events; historical pulls via list endpoints paged with from/to timestamps and order
Capabilities
read · write · webhooks
Rate limits
60 requests per minute per company by default (120/min for Advanced Messaging customers); responses carry X-AircallApi-Limit, X-AircallApi-Remaining, and X-AircallApi-Reset headers
Aircall setup guide

Databricks

Integration surface
SQL over JDBC/ODBC via SQL warehouses, plus a REST API including statement execution
Authentication
Personal access tokens or OAuth machine-to-machine credentials for service principals
Change detection
Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns
Capabilities
read · write · CDC
Rate limits
Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits
How it works

How to connect Aircall to Databricks — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Aircall and Databricks with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Aircall connected
    Databricks connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Aircall and Databricks objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Aircall ⇄ Databricks
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Aircall Databricks
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Aircall and Databricks integration FAQ

SECURITY

Security teams trust Stacksync

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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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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 454 integrations available for Aircall and Databricks.

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