Two-way sync
Changes in Amazon Aurora or Sharepoint instantly reflect in both systems. No stale data, no manual imports.
Keep Amazon Aurora and Sharepoint in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
A database holds structured records; a storage system holds the files those records depend on, such as contracts, images, exports, uploads, and documents. The two describe the same things from opposite sides: a row in Amazon Aurora says a file exists and carries its name, location, and status, while Sharepoint holds the bytes. Linked only by a hand-kept path or a one-off script, the two drift the moment a file is renamed, moved, or deleted and the record still points at where it used to be.
Stacksync syncs Materialized Views, Columns and Data Types, Primary and Foreign Keys, Read Replicas in Amazon Aurora with Sites, Lists, List items, Drive items (document libraries) in Sharepoint bi-directionally and in real time. File attributes, including name, path or object key, size, type, modified time, owner, and tags or custom properties, map field by field to columns on the matching row, and a change on either side shows up on the other within seconds. New files appear as rows, metadata edits travel in the direction you choose, and deletes stay consistent, with conflict rules you set in place of nightly reconciliation scripts.
Every file or object in Sharepoint shows up as a row in Amazon Aurora, with its name, folder or key, size, type, and modified date as columns, so the contents of the store can be listed, filtered, and joined like any other table.
Tags, custom properties, owner, or status columns edited on a row in Amazon Aurora write back to the matching file's metadata in Sharepoint, and metadata changed in Sharepoint updates the row, so the two never disagree about a file.
Where a record in Amazon Aurora references a file in Sharepoint, such as a contract, an image, an export, or an upload, the reference, path, and status stay consistent as files are renamed, moved, or replaced, so stored links keep resolving.
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.
| Amazon Aurora objects | Sharepoint objects | How this pairing syncs | |
|---|---|---|---|
| Tables Relational tables synced bi-directionally at row level. | Site pages Modern site pages via /sites/{id}/pages; read page content, layout, and metadata for indexing and content governance. | Tables is specific to Amazon Aurora and Site pages to Sharepoint — each maps to any object or custom field on the other side. | |
| Views Read-only query-backed sources for downstream syncs. | Sites SharePoint site collections and subsites via /sites; read site properties and discover the document libraries (drives) and lists each site contains, addressed by hostname and site path or site ID. | Views is specific to Amazon Aurora and Sites to Sharepoint — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed result sets (PostgreSQL-compatible clusters) readable as sources. | Lists Custom lists and libraries via /sites/{id}/lists; create and read lists along with their columns and content types so a target system can mirror or provision list definitions. | Materialized Views is specific to Amazon Aurora and Lists to Sharepoint — each maps to any object or custom field on the other side. | |
| Columns and Data Types Standard MySQL or PostgreSQL types mapped during field mapping. | List items Rows in a SharePoint list via /lists/{id}/items with a fields facet of column values; full create, read, update, and delete, synced two-way with database rows. | Columns and Data Types is specific to Amazon Aurora and List items to Sharepoint — each maps to any object or custom field on the other side. | |
| Primary and Foreign Keys Constraints used to identify records and preserve relational integrity in syncs. | Drive items (document libraries) Files and folders in a library's drive via /drives and /drive/root; upload, download, move, delete, and read per-item metadata, synced two-way with a store. | Primary and Foreign Keys is specific to Amazon Aurora and Drive items (document libraries) to Sharepoint — each maps to any object or custom field on the other side. | |
| Read Replicas Reader endpoints that syncs can target to keep load off the writer. | Columns and content types Field definitions and content types on a site or list; read the schema and create columns so database fields map cleanly onto SharePoint list fields. | Read Replicas is specific to Amazon Aurora and Columns and content types to Sharepoint — 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 Amazon Aurora are captured at the source via change data capture — no polling loop against its API. Log-based CDC: binlog on MySQL-compatible clusters, logical replication/decoding on PostgreSQL-compatible clusters.
DeliveryEach detected change is written to Sharepoint through its API, with automatic retries and rate-limit backoff.
DetectionSharepoint notifies Stacksync of record changes through webhook events. Delta query (pull) tracks created, updated, and deleted list items (/lists/{id}/items/delta) and drive items (/drives/{id}/root/delta) since the last.
DeliveryEach detected change is applied to Amazon Aurora as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Amazon Aurora–Sharepoint connection.
Changes in Amazon Aurora or Sharepoint instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Amazon Aurora or Sharepoint data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Amazon Aurora or Sharepoint record.
Track your Amazon Aurora ⇄ Sharepoint sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Amazon Aurora and Sharepoint.
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 Amazon Aurora and Sharepoint 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 Amazon Aurora and Sharepoint 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 425 integrations available for Amazon Aurora and Sharepoint.