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Database ⇄ Accounting and finance

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

Keep Jdbc 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 Jdbc and Ramp

Work with Ramp's financial data straight from Jdbc: read it with ordinary queries, write to it from your own code, and let Stacksync keep both sides consistent.

Engineers need finance data more often than finance systems make it easy to get: for internal tools, reporting services, or logic that reacts to invoices and payments. Working through the vendor API means rate limits, pagination, and glue code that has to be maintained forever.

Stacksync mirrors Transactions, Cards, Users, Departments from Ramp into Schemas & catalogs, Stored procedures & functions, Sequences, Tables in Jdbc and keeps the two in sync bi-directionally and in real time. Your services read finance records with normal queries against Jdbc, and rows your code writes or updates flow back into Ramp with validation, so the finance system stays the system of record.

Common use cases

  • 01 Mirror Bills and their approval and payment state into an AP or ERP system, marking each one ready-to-sync then synced to keep both ledgers reconciled.
  • 02 Read Reimbursements into a finance database for cross-entity expense reporting and reconciliation without manual CSV exports.
  • 03 Connect a niche or legacy RDBMS that has no dedicated Stacksync connector but ships a JDBC driver, using its JDBC URL to sync it two-way.
  • 04 Incrementally sync a high-volume table by polling an updated_at or auto-increment column, keeping a downstream store fresh without full reloads.

Common sync patterns

Internal tools without API plumbing

Build dashboards and back-office tools directly on Jdbc; Stacksync handles the API calls, rate limits, and retries against Ramp.

Write back safely

Updates written to the synced tables in Jdbc propagate into Ramp, so automations can create or correct finance records without custom integration code.

React to financial events

Changes in Ramp appear in Jdbc as row changes, so you can trigger downstream logic with the database tooling you already use.

What you can sync between Jdbc 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.

Jdbc objects Ramp objects How this pairing syncs
Schemas & catalogs Namespaces that group tables and views; the connector targets a schema/catalog and lists its objects from the JDBC metadata to build the sync. Vendors Supplier records under the accounting namespace; uploaded and updated for AP matching and payments. Schemas & catalogs is specific to Jdbc and Vendors to Ramp — each maps to any object or custom field on the other side.
Stored procedures & functions Server-side routines callable via JDBC CallableStatement; invoked for custom read or write logic when a table-level mapping is not enough. Funds (Spend Controls) Spend controls governing card usage; read and created via the funds API to enforce budgets per user, department, or program. Stored procedures & functions is specific to Jdbc and Funds (Spend Controls) to Ramp — each maps to any object or custom field on the other side.
Sequences Server-generated identity values; relevant when writing rows into tables whose keys are assigned by the database rather than the source system. General Ledger Accounts Chart-of-accounts entries uploaded from the ERP; accounting codings are posted back against transactions and bills. Sequences is specific to Jdbc and General Ledger Accounts to Ramp — each maps to any object or custom field on the other side.
Tables The base relational tables in the target database; synced two-way as rows over SQL, with each table's primary key driving upserts and row-level updates. Transactions Card purchase records with merchant, amount, and state; read for spend/GL sync and written back via accounting codings and sync status. Tables is specific to Jdbc and Transactions to Ramp — each maps to any object or custom field on the other side.
Views Stored SELECT queries exposed like tables; read-only projections synced outbound when raw base tables should not be exposed downstream. Cards Physical and virtual card records; created and managed through the API to provision or suspend cardholder spend. Views is specific to Jdbc and Cards to Ramp — each maps to any object or custom field on the other side.
Columns Per-table fields with data types, nullability, and defaults; enumerated via DatabaseMetaData.getColumns to auto-generate and type-check field mappings. Users Employee and cardholder records; invited, updated, and deactivated, commonly synced from an HRIS or identity provider. Columns is specific to Jdbc and Users to Ramp — each maps to any object or custom field on the other side.

How changes propagate between Jdbc 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.

Jdbc Ramp Interval-based propagation

DetectionStacksync polls Jdbc for changes on an incremental schedule, reading only records changed since the previous pass. No native change feed.

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

Ramp Jdbc 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 Jdbc as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Jdbc: No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.
  • 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 Jdbc ⇄ Ramp

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jdbc 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 Jdbc or Ramp record.

Observability

Monitoring

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

Trading partners

EDI

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

How the Jdbc and Ramp connectors work

Jdbc

Integration surface
JDBC API (java.sql / javax.sql) executing SQL through a JDBC driver, typically a pure-Java Type 4 driver; reaches any relational database with a driver - PostgreSQL, MySQL, SQL Server, Oracle, IBM DB2, and others - via a JDBC URL such as jdbc:postgresql://host:5432/db.
Authentication
A database user's username and password supplied in the JDBC connection (DriverManager or a DataSource), typically over a TLS/SSL-encrypted connection. Some drivers add Kerberos, integrated Windows auth, or cloud IAM-token auth, but the available methods depend on the target database and its driver.
Change detection
No native change feed. Incremental sync polls a cursor column - an updated_at timestamp or an auto-incrementing key - to pull new and changed rows; detecting deletes needs soft-delete flags or database triggers writing to a shadow table. No webhooks.
Capabilities
read · write
Rate limits
No SaaS-style request quota. Throughput is bounded by the target database's max connections and connection-pool size, plus the CPU and I/O it shares with production queries, so heavy syncs can contend with live workloads.

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 Jdbc 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 Jdbc 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
    Jdbc connected
    Ramp connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Jdbc and Ramp integration FAQ

SECURITY

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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 426 integrations available for Jdbc and Ramp.

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