Real-time
Two-way sync
Changes in Jdbc or Sage X3 instantly reflect in both systems. No stale data, no manual imports.
Database ⇄ ERP
Jdbc to Sage X3 integration — real-time, two-way sync
Keep Jdbc and Sage X3 in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
- SOC 2 and 6 other compliance frameworks
- POC with real engineers in minutes
Adopted by fast-scaling companies moving mission-critical data in real time
Case study
Migrated from MuleSoft
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Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Jdbc and Sage X3
Give your engineers Sage X3's data in Jdbc: read it with normal queries, write back through the sync, and skip the ERP API entirely.
ERP data sits behind interfaces built for the ERP's own modules, not for your internal systems. Teams that need those records, for reporting services, internal tools, or automations, end up writing integration code against a strict API and maintaining it through every upgrade.
Stacksync mirrors Business Partners (Customers and Suppliers), Products, Sales Orders, Purchase Orders from Sage X3 into Jdbc and keeps both sides consistent in real time. Whatever Sage X3 is the system of record for, whether financials, operations, people, or procurement, those records become rows your code can query, and changes written in Jdbc sync back into Sage X3 with its validations respected.
Common use cases
- 01 Incrementally sync a high-volume table by polling an updated_at or auto-increment column, keeping a downstream store fresh without full reloads.
- 02 Consolidate several databases from different vendors into one relational store by syncing each through its own JDBC driver.
- 03 Push orders from e-commerce or EDI channels into X3 sales orders and return delivery status.
- 04 Publish per-site stock levels to storefronts and a WMS on a schedule.
Common sync patterns
React to ERP changes
Updates in Sage X3 arrive as row changes in Jdbc, so jobs and triggers can respond as the business record changes.
Where Sage X3 is the HR system of record: people data for internal systems
Worker and org records stay current in Jdbc for provisioning, access, and reporting systems that read from the database.
Controlled write-back
Choose exactly which tables and fields may flow from Jdbc back into Sage X3, keeping the ERP authoritative.
What you can sync between Jdbc and Sage X3
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 | Sage X3 objects | How this pairing syncs | |
|---|---|---|---|
| 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. | Purchase Orders Procurement documents synced with supplier-facing systems. | Tables is specific to Jdbc and Purchase Orders to Sage X3 — 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. | Work Orders Production orders read by MES and scheduling integrations. | Views is specific to Jdbc and Work Orders to Sage X3 — 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. | Stock / Inventory by site On-hand and allocated quantities per site, synced to storefronts and WMS. | Columns is specific to Jdbc and Stock / Inventory by site to Sage X3 — each maps to any object or custom field on the other side. | |
| 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. | Bills of Material Product structures read for planning and costing. | Primary keys & indexes is specific to Jdbc and Bills of Material to Sage X3 — 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. | GL Journals Financial entries replicated to warehouses for group reporting. | Schemas & catalogs is specific to Jdbc and GL Journals to Sage X3 — 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. | Deliveries Shipment documents synced to logistics providers and customer portals. | Stored procedures & functions is specific to Jdbc and Deliveries to Sage X3 — each maps to any object or custom field on the other side. |
How changes propagate between Jdbc and Sage X3
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 Sage X3 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 applied to Sage X3 as a row-level write, with types converted between the two schemas.
Sage X3 Jdbc Interval-based propagation
DetectionStacksync polls Sage X3 for changes on an incremental schedule, reading only records changed since the previous pass. Scheduled polling.
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.
What ships with Jdbc ⇄ Sage X3
Connect Jdbc and Sage X3 for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jdbc–Sage X3 connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Jdbc or Sage X3 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 Sage X3 record.
Observability
Monitoring
Track your Jdbc ⇄ Sage X3 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 Sage X3.
How the Jdbc and Sage X3 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.
Sage X3
- Integration surface
- SOAP and REST web services published from X3 business objects; direct SQL access to the underlying database on-prem
- Authentication
- Dedicated web-service user credentials (Basic auth) against configured connection pools
- Change detection
- Scheduled polling; no general webhook surface on the classic web services layer
- Capabilities
- read · write
How it works
How to connect Jdbc to Sage X3 — 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.
- 01
Connect your apps
Authenticate Jdbc and Sage X3 with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Jdbc connected
Sage X3
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Jdbc and Sage X3 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.
objects · Jdbc ⇄ Sage X3Customers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Jdbc Sage X3Company company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Jdbc and Sage X3 integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Jdbc and Sage X3: authenticate both systems, choose the objects to sync (such as Jdbc's Tables and Views), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Jdbc and Sage X3 connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Jdbc–Sage X3 integration in-house.
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Yes — Stacksync ships production-grade connectors for both Jdbc and Sage X3. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Jdbc: 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. On Sage X3: Scheduled polling; no general webhook surface on the classic web services layer. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Jdbc side: Views, Columns, Primary keys & indexes, Schemas & catalogs, plus custom fields where Jdbc exposes them. On the Sage X3 side: Business Partners (Customers and Suppliers), Products, Sales Orders, Purchase Orders. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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.
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS
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:
Related integrations
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