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Data warehouse ⇄ Accounting and finance

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

Keep Databricks and Ramp 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 Databricks and Ramp

Land the financial records from Ramp in Databricks continuously, and write results back, without building or maintaining a pipeline.

Finance data belongs in the warehouse: revenue, invoices, payments, and customers joined with everything else the business measures. Getting it there usually means an extraction pipeline that breaks quietly and delivers yesterday's numbers.

Stacksync syncs Reimbursements, Bills, Vendors, Funds (Spend Controls) from Ramp into tables in Databricks in real time, and the connection works in both directions: values computed in Databricks can be written back to fields in Ramp where you want them operational. Schema changes are handled, API limits are managed, and the sync is something you configure rather than code you maintain.

Common use cases

  • 01 Read Reimbursements into a finance database for cross-entity expense reporting and reconciliation without manual CSV exports.
  • 02 Two-way sync Transactions and their accounting codings with a Postgres warehouse so finance analyzes spend in SQL and pushes GL categories and memos back to Ramp.
  • 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

Queryable history for audit and reconciliation

A continuously synced copy in Databricks gives you a durable, queryable record of financial data for month-end and audit questions.

Finance analytics without ETL

Invoices, payments, and customer records from Ramp arrive in Databricks as queryable tables, current within seconds instead of a day behind.

Revenue joined with everything else

Analysts combine Ramp's financial records with product, marketing, or operational data already in Databricks for reporting the finance system cannot do alone.

What you can sync between Databricks and Ramp

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.

Databricks objects Ramp objects How this pairing syncs
Volumes Unity Catalog file storage used for staging bulk loads. Transactions Card purchase records with merchant, amount, and state; read for spend/GL sync and written back via accounting codings and sync status. Volumes is specific to Databricks and Transactions to Ramp — each maps to any object or custom field on the other side.
SQL Warehouses The compute endpoint a sync connects to for query execution. Cards Physical and virtual card records; created and managed through the API to provision or suspend cardholder spend. SQL Warehouses is specific to Databricks and Cards to Ramp — each maps to any object or custom field on the other side.
Change Data Feed Row-level change records on Delta tables that drive incremental reads. Users Employee and cardholder records; invited, updated, and deactivated, commonly synced from an HRIS or identity provider. Change Data Feed is specific to Databricks and Users to Ramp — each maps to any object or custom field on the other side.
Catalogs Top level of the Unity Catalog namespace, scoping which schemas a sync can address. Departments Org groupings for cost-center and GL allocation; pushed from an ERP/HRIS and referenced by cards and transactions. Catalogs is specific to Databricks and Departments to Ramp — each maps to any object or custom field on the other side.
Schemas Group tables and views; syncs typically target a dedicated schema per source system. Reimbursements Out-of-pocket expense claims; read for reporting and marked ready-to-sync then synced to the ERP. Schemas is specific to Databricks and Reimbursements to Ramp — each maps to any object or custom field on the other side.
Delta Tables The primary read and write target; operational data lands here as managed or external tables. Bills Accounts-payable bills; created, updated, approved, and paid, then posted ready-to-sync and synced to accounting. Delta Tables is specific to Databricks and Bills to Ramp — each maps to any object or custom field on the other side.

How changes propagate between Databricks and Ramp

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.

Databricks Ramp 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 Ramp through its API, with automatic retries and rate-limit backoff.

Ramp Databricks Sub-second propagation

DetectionRamp notifies Stacksync of record changes through webhook events. Signed webhooks (HMAC-SHA256 X-Ramp-Signature) for bill, transaction, reimbursement, vendor, and user events.

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

Rate-limit considerations

  • Databricks: Throughput depends on the SQL warehouse size; API calls are subject to workspace rate limits.
  • Ramp: 200 requests per 10-second rolling window per source IP; exceeding it returns 429 Too Many Requests, and requests running over 60 seconds return 504. Results use keyset pagination (follow the page.next URL / start cursor); higher limits can be requested from support.
What ships with Databricks ⇄ Ramp

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Databricks or Ramp 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 Databricks or Ramp record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Databricks and Ramp connectors work

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

Ramp

Integration surface
REST API (Developer API v1)
Authentication
OAuth 2.0: exchange client_id/client_secret (HTTP Basic) at api.ramp.com/developer/v1/token for scoped bearer tokens; client_credentials grant for server-to-server and authorization_code for user-delegated access; scopes follow resource:permission (e.g. transactions:read, bills:write, accounting:write).
Change detection
Signed webhooks (HMAC-SHA256 X-Ramp-Signature) for bill, transaction, reimbursement, vendor, and user events; otherwise poll incrementally (synced_after on transactions, from_created_at on bills) with keyset pagination, or read the audit-logs/events feed.
Capabilities
read · write · webhooks
Rate limits
200 requests per 10-second rolling window per source IP; exceeding it returns 429 Too Many Requests, and requests running over 60 seconds return 504. Results use keyset pagination (follow the page.next URL / start cursor); higher limits can be requested from support.
Ramp setup guide
How it works

How to connect Databricks to Ramp — 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 Databricks and Ramp 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
    Databricks connected
    Ramp connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Databricks and Ramp 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 · Databricks ⇄ Ramp
    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
    Databricks Ramp
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Databricks and Ramp 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 545 integrations available for Databricks and Ramp.

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