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One Pipeline Layer for Every Data Movement Pattern
DataJump is the productized enterprise data pipeline engine for enterprise-wide data delivery, spanning Oracle, non-Oracle, SaaS, databases, files, streams, and modern analytics destinations.
Multi-Source Ingestion
Connect to operational applications, legacy systems, SaaS platforms, databases, and file stores with a common pipeline experience.
High-Throughput Replication
Move data into the platforms your business depends on for analytics, reporting, lakehouse engineering, synchronization, and AI-ready data products.
Governed Orchestration
Automate dependencies, transformations, publishing, scheduling, and monitoring so teams can operationalize pipelines with repeatable controls.
Architecture
From Connector to Business-Ready Enterprise Data
A generic, product-led view of the pipeline — from diverse source systems through DataJump and orchestration, out to whichever platform the business uses.
Source layer
Business applications, packaged adapters, databases, APIs, files, object stores, and event streams.
DataJump
Extraction, replication, schema-aware ingestion, load handling, and reusable pipeline templates.
Orchestration
DataFlow or JobFlow execution, dependencies, transforms, scheduling, and operational control.
Delivery layer
Warehouses, lakehouses, BI tools, reports, spreadsheets, data products, and downstream applications.
How It Works
Connect Once, Run with Confidence
A repeatable lifecycle that takes teams from standardized connections through reusable pipelines and consumption-ready data, all under operational control.
Connect Once
Standardize authentication,
authorization, security, and metadata across source systems.
Design Reusable Pipelines
Package repeatable extraction and replication patterns so every team does not rebuild from scratch.
Transform for Consumption
Prepare data for warehouse
analytics, operational dashboards, Excel reporting, or app-to-app delivery.
Run with Confidence
Monitor dependencies, schedules, delivery status, and data quality signals across business-critical pipelines.
Connector Coverage
Built for More Than EBS and Fusion Cloud
Orbit spans a broad connector ecosystem across enterprise applications, cloud services, databases, files, streams, and analytics targets, all managed as governed enterprise data pipelines.
Applications- Oracle Fusion Cloud
- Oracle E-Business Suite
- PeopleSoft · NetSuite
- JD Edwards
- Salesforce
- MS Dynamics CRM
- SAP ECC / S/4 HANA
- SAP SuccessFactors
- Custom business apps
Databases- Oracle · MySQL
- PostgreSQL
- MongoDB
- Cassandra
- SQL warehouses
- NoSQL platforms
Cloud & files- Amazon S3
- Azure Blob / ADLS
- Google Cloud Storage
- Drive · Box · Dropbox
- FTP / SFTP
- Delimited files
- Parquet · Avro / ORC
Streams & big data- Apache Kafka
- Amazon Kinesis
- Google Pub/Sub
- MQTT
- Apache Hive
- MapReduce
- Cloudera / Hadoop
Analytics targets- Oracle ADW
- Snowflake
- Databricks
- Amazon Redshift
- Google BigQuery
- Power BI
- Orbit reporting
Product Message
200+ Connector Ecosystem Across Every Source and Destination
DataJump is the repeatable bridge between every source and every analytical outcome.
Keep Oracle strengths visible, but make the page about enterprise pipeline coverage: source diversity, governed replication, orchestration, and delivery into whichever platform the business uses.
Pipeline Templates for Common Business Patterns
Package repeatable logic for finance, HR, supply chain, sales, operations, and cross-application analytics.
Schema-Aware Ingestion
Reduce brittle hand-coded jobs by handling metadata and schema changes in a managed pipeline framework.
Hybrid Deployment Fit
Support cloud, on-premise, embedded, and hybrid operating models so pipelines align to customer architecture.
Operational Visibility
Give data teams a single place to understand dependencies, runs, failures, and downstream readiness.
Security by Design
Centralize authentication, authorization, permission-based access, and controlled data movement across connectors.
Analytics and Reporting Delivery
Serve cloud warehouses, lakehouses, BI dashboards, Excel workbooks, operational reports, and downstream apps.
Use Cases
Designed for Real Enterprise Pipeline Scenarios
Use these blocks to replace Fusion-only examples with a broader product story.
Multi-ERP Analytics Foundation
Combine Oracle, NetSuite, PeopleSoft, SAP, and legacy operational systems into a governed warehouse or lakehouse.
SaaS and CRM Pipeline Delivery
Replicate sales, marketing, customer, and operational application data into centralized analytics platforms.
Finance and Operations Reporting
Feed trusted reporting models, Excel refresh workflows, PDFs, dashboards, and department- level analytics.
AI-Ready Lakehouse Data Products
Deliver curated data to Databricks, Fabric, BigQuery, and other lakehouse or cloud analytics platforms.
Legacy Modernization
Move data from older ERP, custom applications, files, and databases into modern architectures while preserving continuity.
Application Synchronization
Use governed pipelines to support business process synchronization across departments and downstream systems.
Frequently Asked Questions
An enterprise data pipeline moves data from source systems such as ERP, CRM, and databases into destinations like warehouses, lakehouses, and BI tools, with scheduling, monitoring, and governance built in. Orbit DataJump provides this as a repeatable pipeline layer across every connector.
Orbit DataJump is Orbit's data pipeline product for extraction, replication, schema-aware ingestion, and load handling. It uses reusable pipeline templates and orchestration so teams do not rebuild integrations from scratch for each source or destination.
DataJump connects to Oracle E-Business Suite, Oracle Fusion Cloud, PeopleSoft, NetSuite, JD Edwards, Salesforce, SAP, databases, files, and streams, and delivers to Oracle ADW, Snowflake, Databricks, Amazon Redshift, Microsoft Fabric, Google BigQuery, and Power BI. In total Orbit offers 200+ prebuilt connectors and can build custom connectors on demand.
Orbit connects natively to Oracle EBS and Fusion Cloud, understands their schema, and handles schema changes automatically, so Oracle ERP data pipelines require less hand-coding. MARTA uses Orbit DataJump to move Oracle Fusion data into Databricks.
ETL extracts data, transforms it, then loads it into the target, while ELT loads raw data first and transforms it inside the destination. DataJump supports both patterns with real-time delivery, so teams choose the approach that fits each warehouse or lakehouse.
Yes. DataJump fits cloud, on-premise, embedded, and hybrid operating models, so pipelines align to your existing architecture rather than forcing a single deployment style.
DataJump centralizes authentication, authorization, and permission-based access across connectors, and provides monitoring of dependencies, schedules, delivery status, and data quality. This gives data teams governed, business-critical pipelines with end-to-end control.
