Two-way sync
Changes in Apache Hive or Oracle Fusion Cloud HCM instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Hive and Oracle Fusion Cloud HCM in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Workforce data is some of the most requested data in the warehouse and some of the most awkward to move: the record types are many, the fields carry sensitive personal information, the APIs are strict, and hand-built extract jobs go stale or break quietly. Whether Oracle Fusion Cloud HCM is the system of record for employees and payroll, for candidates and applications, or for learners and course completions, the reporting belongs in Apache Hive next to everything else the company measures.
Stacksync syncs Assignments, Jobs, Positions, Departments (Organizations) from Oracle Fusion Cloud HCM into tables in Apache Hive continuously, handling API limits and schema drift as they come. The connection is bi-directional, so values computed in Apache Hive, such as headcount rollups, cost allocations, or attrition risk flags, can be written back to fields in Oracle Fusion Cloud HCM where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.
Analysts combine Oracle Fusion Cloud HCM's workforce records with finance, product, or operational data already in Apache Hive for reporting the HR system cannot produce on its own.
Because changes stream continuously, reports query current workforce data rather than waiting for an overnight load window to finish.
A continuously synced copy in Apache Hive gives you a durable, queryable record of how Oracle Fusion Cloud HCM's records change over time, for headcount planning and audit questions.
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.
| Apache Hive objects | Oracle Fusion Cloud HCM objects | How this pairing syncs | |
|---|---|---|---|
| External Tables Tables over existing files in HDFS or object storage, read without moving data. | Locations Physical work locations referenced by assignments; synced so downstream provisioning and directory tools resolve the same location codes. | External Tables is specific to Apache Hive and Locations to Oracle Fusion Cloud HCM — each maps to any object or custom field on the other side. | |
| Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. | Grades and Salaries Grade, grade-rate, and worker compensation records; usually read out for compensation and headcount analytics, and written back for corrections. | Partitions is specific to Apache Hive and Grades and Salaries to Oracle Fusion Cloud HCM — each maps to any object or custom field on the other side. | |
| Views Logical views readable as modeled sources. | Absences (workerAbsenceEntries) Time-off and leave entries; synced into scheduling or workforce-management databases for coverage planning. | Views is specific to Apache Hive and Absences (workerAbsenceEntries) to Oracle Fusion Cloud HCM — each maps to any object or custom field on the other side. | |
| Materialized Views Precomputed results available in newer Hive versions for faster reads. | Workers (publicWorkers) Person master with personNumber, names, national IDs, and work relationships; synced two-way via the /workers resource, which replaced the desupported /emps resource. | Materialized Views is specific to Apache Hive and Workers (publicWorkers) to Oracle Fusion Cloud HCM — each maps to any object or custom field on the other side. | |
| ACID Tables ORC-backed transactional tables that support row-level insert, update, and delete. | Assignments Child of a worker's work relationship carrying job, position, department, location, grade, and manager; effective-dated, so writes go through PATCH with an effective date. | ACID Tables is specific to Apache Hive and Assignments to Oracle Fusion Cloud HCM — each maps to any object or custom field on the other side. | |
| Metastore Catalog The schema registry other engines (Spark, Presto, Impala) also read. | Jobs Job catalog reference data; commonly read out to align titles and job codes in a warehouse or written to keep downstream systems consistent. | Metastore Catalog is specific to Apache Hive and Jobs to Oracle Fusion Cloud HCM — 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 Apache Hive for changes on an incremental schedule, reading only records changed since the previous pass. Polling on partition values or timestamp columns.
DeliveryEach detected change is written to Oracle Fusion Cloud HCM through its API, with automatic retries and rate-limit backoff.
DetectionChanges in Oracle Fusion Cloud HCM are captured at the source via change data capture — no polling loop against its API. Atom feeds expose changes-only feeds for key events (new hire, termination, assignment change).
DeliveryEach detected change is applied to Apache Hive as a row-level write, with types converted between the two schemas.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Hive–Oracle Fusion Cloud HCM connection.
Changes in Apache Hive or Oracle Fusion Cloud HCM instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Hive or Oracle Fusion Cloud HCM data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Hive or Oracle Fusion Cloud HCM record.
Track your Apache Hive ⇄ Oracle Fusion Cloud HCM sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Hive and Oracle Fusion Cloud HCM.
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 Apache Hive and Oracle Fusion Cloud HCM 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 Apache Hive and Oracle Fusion Cloud HCM 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.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Hive and Oracle Fusion Cloud HCM: authenticate both systems, choose the objects to sync (such as Apache Hive's External Tables and Partitions), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Apache Hive: Polling on partition values or timestamp columns; no general-purpose change log for external consumers. On Oracle Fusion Cloud HCM: Atom feeds expose changes-only feeds for key events (new hire, termination, assignment change); REST q= filters on LastUpdateDate and HCM Extract in incremental mode cover broader deltas. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Apache Hive side: Materialized Views, ACID Tables, Metastore Catalog, Databases, plus custom fields where Apache Hive exposes them. On the Oracle Fusion Cloud HCM side: Assignments, Jobs, Positions, Departments (Organizations). Stacksync auto-detects both schemas and converts types between the two systems.
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.
Common patterns for Apache Hive and Oracle Fusion Cloud HCM: Headcount and cost joined with everything else; Fresh data instead of last night's load; Queryable history for planning and audit. Analysts combine Oracle Fusion Cloud HCM's workforce records with finance, product, or operational data already in Apache Hive for reporting the HR system cannot produce on its own.
Apache Hive: SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift). Authentication: Deployment-dependent: Kerberos, LDAP, or username/password. Oracle Fusion Cloud HCM: REST API (/hcmRestApi/resources), Atom feeds, and HCM Data Loader (HDL) for bulk. Authentication: OAuth 2.0 bearer tokens via Oracle Identity Cloud Service (IDCS/IAM); HTTP Basic and SAML/JWT bearer over SSL are also accepted, enforced by Oracle Web Services Manager (OWSM). Stacksync manages authentication, retries, and rate limits on both sides.
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.
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Every pair below is a real-time, two-way sync. Search all 439 integrations available for Apache Hive and Oracle Fusion Cloud HCM.