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Jdbc to SAP Hana integration — real-time, two-way sync

Keep Jdbc and SAP Hana 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 Jdbc and SAP Hana

Keep Jdbc and SAP Hana synchronized in real time, across engines, regions, or services, in one or both directions.

Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.

Stacksync syncs tables or collections between Jdbc and SAP Hana continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.

Common use cases

  • 01 Consolidate several databases from different vendors into one relational store by syncing each through its own JDBC driver.
  • 02 Write records from a CRM, ERP, or another app back into database tables via SQL INSERT and UPDATE so the database stays current.
  • 03 Read SYS.TABLES and TABLE_COLUMNS system views to auto-discover schema and generate field mappings when new tables are added to the sync.
  • 04 Detect inserts, updates, and deletes on high-write tables via AFTER triggers or a last-modified column and replicate the deltas downstream near-real-time.

Common sync patterns

Shared reference data between services

Services that own separate databases stay consistent on the records they share, without a custom replication layer.

Regional or environment copies

Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.

Cross-engine sync

Keep the same dataset live in both Jdbc and SAP Hana, so each workload runs on the engine that suits it.

What you can sync between Jdbc and SAP Hana

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 SAP Hana objects How this pairing syncs
Sequences Server-generated identity values; relevant when writing rows into tables whose keys are assigned by the database rather than the source system. Sequences Server-generated key values; relevant when writing rows into tables whose identity is assigned HANA-side rather than by the source system. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
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. Row store tables OLTP-oriented tables held fully in memory; read and written the same way through the SAP HANA client for high-write operational tables. Primary keys & indexes is specific to Jdbc and Row store tables to SAP Hana — 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. Calculation views Modeled analytic views over base tables; read-only sources for pushing aggregated or joined results into a warehouse or downstream app. Schemas & catalogs is specific to Jdbc and Calculation views to SAP Hana — 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. SQL views Standard database views; read-only projections synced outbound when the source data should not be exposed as raw base tables. Stored procedures & functions is specific to Jdbc and SQL views to SAP Hana — 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. Schemas Namespaces that group tables and views; the connector targets a schema and enumerates its objects from the catalog to build the sync. Tables is specific to Jdbc and Schemas to SAP Hana — 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. Triggers AFTER INSERT/UPDATE/DELETE triggers capture changes into a shadow/logging table so updates and deletes are detected near-real-time without full scans. Views is specific to Jdbc and Triggers to SAP Hana — each maps to any object or custom field on the other side.

How changes propagate between Jdbc and SAP Hana

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 SAP Hana 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 SAP Hana as a row-level write, with types converted between the two schemas.

SAP Hana Jdbc Sub-second propagation

DetectionChanges in SAP Hana are captured at the source via change data capture — no polling loop against its API. Polling on a last-modified timestamp column, or AFTER INSERT/UPDATE/DELETE triggers writing to a shadow table.

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.
  • SAP Hana: No SaaS-style request quota; throughput is bounded by connection limits, statement memory caps, and workload-class admission control (concurrency/memory limits) that share capacity with production queries.
What ships with Jdbc ⇄ SAP Hana

Connect Jdbc and SAP Hana for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Jdbc–SAP Hana connection.

Real-time

Two-way sync

Changes in Jdbc or SAP Hana instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Jdbc or SAP Hana 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 SAP Hana record.

Observability

Monitoring

Track your Jdbc ⇄ SAP Hana 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 SAP Hana.

How the Jdbc and SAP Hana 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.

SAP Hana

Integration surface
SQL over the SAP HANA client (JDBC/ODBC drivers); OData/REST via XS for app-layer access
Authentication
Dedicated database user credentials over an encrypted TLS connection (password sent hashed); Kerberos, SAML, JWT, and X.509 certificate authentication are also supported. SAP HANA Cloud enforces TLS and IP allowlisting.
Change detection
Polling on a last-modified timestamp column, or AFTER INSERT/UPDATE/DELETE triggers writing to a shadow table; system-versioned temporal tables and SLT/SDI provide trigger- and log-based CDC. No native webhooks.
Capabilities
read · write · CDC
Rate limits
No SaaS-style request quota; throughput is bounded by connection limits, statement memory caps, and workload-class admission control (concurrency/memory limits) that share capacity with production queries.
How it works

How to connect Jdbc to SAP Hana — 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 Jdbc and SAP Hana 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
    Jdbc connected
    SAP Hana connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Jdbc and SAP Hana 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 · Jdbc ⇄ SAP Hana
    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
    Jdbc SAP Hana
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Jdbc and SAP Hana 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.

Learn more about security
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:

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 465 integrations available for Jdbc and SAP Hana.

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