Two-way sync
Changes in AWS Aurora MySQL or Navan instantly reflect in both systems. No stale data, no manual imports.
Keep AWS Aurora MySQL and Navan in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 Bookings, Custom Fields, Receipts, Repayments, Fees, and Adjustments from Navan into Tables, Rows, Columns, Primary keys and indexes in AWS Aurora MySQL and keeps the two in sync bi-directionally and in real time. Your services read finance records with normal queries against AWS Aurora MySQL, and rows your code writes or updates flow back into Navan with validation, so the finance system stays the system of record.
Customers, invoices, and payments from Navan live in AWS Aurora MySQL as regular tables or collections your team can join, index, and query.
Build dashboards and back-office tools directly on AWS Aurora MySQL; Stacksync handles the API calls, rate limits, and retries against Navan.
Updates written to the synced tables in AWS Aurora MySQL propagate into Navan, so automations can create or correct finance records without custom integration code.
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 MySQL objects | Navan objects | How this pairing syncs | |
|---|---|---|---|
| Rows Inserted, updated, and deleted individually or in bulk during two-way syncs. | Connect Transactions External and personal card feed matched into Navan; retrieved read-only and coded with custom-field values through the transaction update endpoint. | Rows is specific to AWS Aurora MySQL and Connect Transactions to Navan — each maps to any object or custom field on the other side. | |
| Columns MySQL data types are mapped to the paired system's field types during schema setup. | Manual Transactions Out-of-pocket reimbursements and payroll submissions; synced for approval and reimbursement, then GL-coded back into Navan. | Columns is specific to AWS Aurora MySQL and Manual Transactions to Navan — each maps to any object or custom field on the other side. | |
| Primary keys and indexes Used to match rows across systems and keep incremental syncs efficient. | Bookings Flight, hotel, rail, and car reservations from the Booking API; pulled read-only by createdFrom/createdTo date range for trip and travel-spend reporting. | Primary keys and indexes is specific to AWS Aurora MySQL and Bookings to Navan — each maps to any object or custom field on the other side. | |
| Views Can serve as read-only sync sources for derived or filtered datasets. | Custom Fields Company metadata such as cost centers and project codes; discovered via GET and their option lists created or updated via async POST. | Views is specific to AWS Aurora MySQL and Custom Fields to Navan — each maps to any object or custom field on the other side. | |
| Foreign keys Express relationships that syncs preserve when mapping to related objects elsewhere. | Receipts Receipt images tied to each transaction; fetched read-only through presigned URLs for archival in a warehouse or document store. | Foreign keys is specific to AWS Aurora MySQL and Receipts to Navan — each maps to any object or custom field on the other side. | |
| Stored procedures and triggers Existing database logic keeps firing on rows written by a sync. | Repayments, Fees, and Adjustments Money-movement records including repayments, FX and platform fees, and credit or debit memos; read-only for reconciliation ledgers. | Stored procedures and triggers is specific to AWS Aurora MySQL and Repayments, Fees, and Adjustments to Navan — each maps to any object or custom field on the other side. |
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.
DetectionChanges in AWS Aurora MySQL are captured at the source via change data capture — no polling loop against its API. Log-based CDC via the MySQL binary log (binlog), with polling on timestamp columns as a fallback.
DeliveryEach detected change is written to Navan through its API, with automatic retries and rate-limit backoff.
DetectionNavan notifies Stacksync of record changes through webhook events. Navan's Expense API supports webhooks for transaction and expense events.
DeliveryEach detected change is applied to AWS Aurora MySQL as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every AWS Aurora MySQL–Navan connection.
Changes in AWS Aurora MySQL or Navan instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever AWS Aurora MySQL or Navan data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single AWS Aurora MySQL or Navan record.
Track your AWS Aurora MySQL ⇄ Navan sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between AWS Aurora MySQL and Navan.
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.
Authenticate AWS Aurora MySQL and Navan with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the AWS Aurora MySQL and Navan 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 445 integrations available for AWS Aurora MySQL and Navan.