Real-time
Two-way sync
Changes in Box or Databricks instantly reflect in both systems. No stale data, no manual imports.
Storage ⇄ Data warehouse
Box to Databricks integration — real-time, two-way sync
Keep Box 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.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Box and Databricks
Bridge query-ready tables and stored files: Databricks and Box keep the same records in step, in real time, in both directions.
Databricks keeps the tables and query results a business reports on; Box keeps the raw files, documents, and objects that the same business produces and shares. The two overlap wherever a dataset lives as both — a file dropped in Box that has to become rows in Databricks, or a result in Databricks that people downstream need back as a file in Box. When that overlap is bridged by manual export and import or an overnight job, one side spends the day working from a stale copy.
Stacksync syncs Views, Materialized Views, Volumes, SQL Warehouses in Databricks with Metadata, Collaborations, Users, Groups in Box field by field, in real time, and in both directions. You decide which system owns which fields; Stacksync keeps every copy consistent and resolves conflicts by rules you set.
Common use cases
- 01 Land CRM and ERP records in Delta tables continuously so lakehouse models work from current operational data.
- 02 Use Change Data Feed to propagate only changed rows to downstream apps instead of full-table scans.
- 03 Push generated documents from an ERP or contract system into Box Folders with the right Collaborations applied for the deal team.
- 04 Stream enterprise Events (admin events) into a warehouse for audit, DLP, and access-review reporting.
Common sync patterns
One dataset, kept consistent both ways
Where the same dataset lives as a file in Box and a table in Databricks, a change on either side propagates to the other, ending the drift between the file people read and the table people query.
Where Box holds the file inventory: make it queryable
The catalog of documents, owners, and folders in Box appears as Views, Materialized Views, Volumes, SQL Warehouses in Databricks, so file metadata can be joined against the rest of your data and reported on.
Where Databricks computes the labels: push them onto the files
Classifications, scores, or status derived in Databricks are written back onto the matching Metadata, Collaborations, Users, Groups in Box as metadata or tags, so the file store reflects what analytics decided.
What you can sync between Box 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.
| Box objects | Databricks objects | How this pairing syncs | |
|---|---|---|---|
| Files Core content object with versions, name, size, and metadata; synced two-way so files and their attributes move between Box and a database or another store. | Materialized Views Precomputed results read on a schedule for reverse-ETL style syncs. | Files is specific to Box and Materialized Views to Databricks — each maps to any object or custom field on the other side. | |
| Folders Hierarchical containers whose tree, names, and parent moves are mirrored so a target system reflects Box's structure; the account root is always folder ID 0. | Volumes Unity Catalog file storage used for staging bulk loads. | Folders is specific to Box and Volumes to Databricks — each maps to any object or custom field on the other side. | |
| Metadata Structured key-value instances attached to files and folders via metadata templates; synced two-way with database columns for classification and search. | SQL Warehouses The compute endpoint a sync connects to for query execution. | Metadata is specific to Box and SQL Warehouses to Databricks — each maps to any object or custom field on the other side. | |
| Collaborations Access grants linking a user or group to a file or folder with a role such as viewer, editor, or co-owner; written to manage sharing programmatically. | Change Data Feed Row-level change records on Delta tables that drive incremental reads. | Collaborations is specific to Box and Change Data Feed to Databricks — each maps to any object or custom field on the other side. | |
| Users Managed and app users in the enterprise; provisioned, updated, and deprovisioned to keep Box access aligned with an HR or identity source. | Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. | Users is specific to Box and Catalogs to Databricks — each maps to any object or custom field on the other side. | |
| Groups Named user collections used for bulk collaboration; membership synced from a directory or IdP. | Schemas Group tables and views; syncs typically target a dedicated schema per source system. | Groups is specific to Box and Schemas to Databricks — each maps to any object or custom field on the other side. |
How changes propagate between Box 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.
Box Databricks Sub-second propagation
DetectionBox notifies Stacksync of record changes through webhook events. V2 webhooks fire on triggers such as FILE.UPLOADED, FILE.TRASHED, and METADATA_INSTANCE.UPDATED.
DeliveryEach detected change is applied to Databricks as a row-level write, with types converted between the two schemas.
Databricks Box 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 Box through its API, with automatic retries and rate-limit backoff.
Rate-limit considerations
- Box: Per user: 1,000 API calls per minute and 240 file uploads per minute; exceeding limits returns HTTP 429 with a Retry-After header. Box Business plans also carry a licensed monthly API-call allotment per enterprise.
- Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
What ships with Box ⇄ Databricks
Connect Box and Databricks for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Box–Databricks connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Box 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 Box or Databricks record.
Observability
Monitoring
Track your Box ⇄ Databricks sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between Box and Databricks.
How the Box and Databricks connectors work
Box
- Integration surface
- REST API (api.box.com/2.0), plus the Events API and V2 Webhooks
- Authentication
- OAuth 2.0 for user-delegated access, or server-to-server auth via JWT (RSA keypair) or Client Credentials Grant (CCG) using a Box app; short-lived developer tokens for testing
- Change detection
- V2 webhooks fire on triggers such as FILE.UPLOADED, FILE.TRASHED, and METADATA_INSTANCE.UPDATED; the Events API (user stream via long-poll by stream_position, or enterprise/admin events) provides a near-real-time change feed
- Capabilities
- read · write · webhooks
- Rate limits
- Per user: 1,000 API calls per minute and 240 file uploads per minute; exceeding limits returns HTTP 429 with a Retry-After header. Box Business plans also carry a licensed monthly API-call allotment per enterprise.
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 Box 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.
- 01
Connect your apps
Authenticate Box 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.
Box
connected
Databricks
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Box 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.
objects · Box ⇄ DatabricksCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Box DatabricksCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Box and Databricks integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Box and Databricks: authenticate both systems, choose the objects to sync (such as Box's Files and Folders), map fields visually, and changes propagate both ways in milliseconds — no code required.
-
Databricks: Delta Lake's Change Data Feed records row-level inserts, updates, and deletes, enabling incremental sync without full scans. Box: The user Events API is consumed with a stream_position and long-polling; enterprise/admin events retain roughly one year of history and can lag strict ordering for near-real-time reads. Stacksync's field mapping accounts for these differences between Box and Databricks without custom code.
-
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Box and Databricks records are not retained after a sync operation.
-
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Box and Databricks connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Box–Databricks integration in-house.
-
Yes — Stacksync ships production-grade connectors for both Box and Databricks. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
-
Change detection on Box: V2 webhooks fire on triggers such as FILE.UPLOADED, FILE.TRASHED, and METADATA_INSTANCE.UPDATED; the Events API (user stream via long-poll by stream_position, or enterprise/admin events) provides a near-real-time change feed. On Databricks: Delta Lake Change Data Feed for row-level changes; otherwise incremental polling on watermark columns. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
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:
Related integrations
Every pair below is a real-time, two-way sync. Search all 541 integrations available for Box and Databricks.
Popular · 7 of 541
-
Box ⇄ Apache Pinot -
Box ⇄ Azure Synapse Analytics -
Box ⇄ ClickHouse -
Box ⇄ Cloudera Data Platform -
Databricks ⇄ Sharepoint -
Databricks ⇄ Egnyte -
Databricks ⇄ Amazon S3
No integrations match .
