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Database ⇄ Accounting and finance

AWS Aurora PostgreSQL to Ramp integration — real-time, two-way sync

Keep AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL and Ramp

Work with Ramp's financial data straight from AWS Aurora PostgreSQL: 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 Reimbursements, Bills, Vendors, Funds (Spend Controls) from Ramp into Databases and schemas, Tables, Rows, Columns in AWS Aurora PostgreSQL and keeps the two in sync bi-directionally and in real time. Your services read finance records with normal queries against AWS Aurora PostgreSQL, 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 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.
  • 02 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.
  • 03 Keep a customer-facing Aurora database aligned with an internal admin tool, with writes accepted on both sides.
  • 04 Feed operational dashboards from a read replica while the writer handles sync traffic.

Common sync patterns

Query finance data like any other data

Customers, invoices, and payments from Ramp live in AWS Aurora PostgreSQL as regular tables or collections your team can join, index, and query.

Internal tools without API plumbing

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

Write back safely

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

What you can sync between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL objects Ramp objects How this pairing syncs
Databases and schemas PostgreSQL's two-level namespace scopes which tables a sync connection targets. General Ledger Accounts Chart-of-accounts entries uploaded from the ERP; accounting codings are posted back against transactions and bills. Databases and schemas is specific to AWS Aurora PostgreSQL and General Ledger Accounts to Ramp — each maps to any object or custom field on the other side.
Tables The core sync unit; rows are matched across systems by primary key. 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 AWS Aurora PostgreSQL and Transactions to Ramp — each maps to any object or custom field on the other side.
Rows Inserted, updated, and deleted in both directions during bi-directional syncs. Cards Physical and virtual card records; created and managed through the API to provision or suspend cardholder spend. Rows is specific to AWS Aurora PostgreSQL and Cards to Ramp — each maps to any object or custom field on the other side.
Columns Rich Postgres types including JSONB and arrays are mapped to the paired system's fields. Users Employee and cardholder records; invited, updated, and deactivated, commonly synced from an HRIS or identity provider. Columns is specific to AWS Aurora PostgreSQL and Users to Ramp — each maps to any object or custom field on the other side.
Primary keys and constraints Identify rows for upserts and enforce integrity on sync writes. Departments Org groupings for cost-center and GL allocation; pushed from an ERP/HRIS and referenced by cards and transactions. Primary keys and constraints is specific to AWS Aurora PostgreSQL and Departments to Ramp — each maps to any object or custom field on the other side.
Views and materialized views Usable as read-only sources for filtered or precomputed sync datasets. Reimbursements Out-of-pocket expense claims; read for reporting and marked ready-to-sync then synced to the ERP. Views and materialized views is specific to AWS Aurora PostgreSQL and Reimbursements to Ramp — each maps to any object or custom field on the other side.

How changes propagate between AWS Aurora PostgreSQL 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.

AWS Aurora PostgreSQL Ramp Sub-second propagation

DetectionChanges in AWS Aurora PostgreSQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback.

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

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

Rate-limit considerations

  • 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 AWS Aurora PostgreSQL ⇄ Ramp

Connect AWS Aurora PostgreSQL and Ramp for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL or Ramp record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between AWS Aurora PostgreSQL and Ramp.

How the AWS Aurora PostgreSQL and Ramp connectors work

AWS Aurora PostgreSQL

Integration surface
SQL wire protocol (PostgreSQL-compatible), standard Postgres drivers and JDBC
Authentication
Database credentials, optionally AWS IAM database authentication, over TLS
Change detection
Log-based CDC via PostgreSQL logical replication (WAL decoding through replication slots), with timestamp polling as a fallback
Capabilities
read · write · CDC

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 AWS Aurora PostgreSQL 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 AWS Aurora PostgreSQL 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
    AWS Aurora PostgreSQL connected
    Ramp connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

AWS Aurora PostgreSQL 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 447 integrations available for AWS Aurora PostgreSQL and Ramp.

Popular · 8 of 447
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