Two-way sync
Changes in Jdbc or Sharepoint instantly reflect in both systems. No stale data, no manual imports.
Keep Jdbc 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 Jdbc 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 Tables, Views, Columns, Primary keys & indexes in Jdbc with Permissions and sharing, Site pages, Sites, Lists 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.
Tags, custom properties, owner, or status columns edited on a row in Jdbc 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 Jdbc 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.
Files that arrive in a folder or bucket in Sharepoint become rows in Jdbc as they land, so a database-driven process can pick them up without polling the storage system's API.
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 | Sharepoint objects | How this pairing syncs | |
|---|---|---|---|
| Primary keys & indexes Key and index definitions read via DatabaseMetaData; the primary key is required for reliable upserts, and indexes on the cursor column keep incremental polling fast. | Permissions and sharing Role assignments and sharing links on sites, list items, and drive items; read and written to manage access, requiring Sites.Manage.All or Sites.FullControl.All scopes. | Primary keys & indexes is specific to Jdbc and Permissions and sharing to Sharepoint — each maps to any object or custom field on the other side. | |
| 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. | Site pages Modern site pages via /sites/{id}/pages; read page content, layout, and metadata for indexing and content governance. | Schemas & catalogs is specific to Jdbc and Site pages to Sharepoint — 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. | 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. | Stored procedures & functions is specific to Jdbc and Sites to Sharepoint — 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. | 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. | Sequences is specific to Jdbc and Lists to Sharepoint — 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. | 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. | Tables is specific to Jdbc and List items to Sharepoint — 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. | 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. | Views is specific to Jdbc and Drive items (document libraries) 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.
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 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 Jdbc as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jdbc–Sharepoint connection.
Changes in Jdbc or Sharepoint instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Jdbc 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 Jdbc or Sharepoint record.
Track your Jdbc ⇄ Sharepoint sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Jdbc 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 Jdbc 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 Jdbc 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 422 integrations available for Jdbc and Sharepoint.