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Data warehouse ⇄ Human resources

Apache Hive to Paylocity integration — real-time, two-way sync

Keep Apache Hive and Paylocity 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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Why teams connect Apache Hive and Paylocity

Land the people and organization records from Paylocity in Apache Hive as live tables for workforce reporting, without extract jobs, and write computed results back where Paylocity can use them.

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 Paylocity 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 Local and State Taxes, Direct Deposit, Pay Statements, Company Codes from Paylocity 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 Paylocity where the HR team acts on them. You configure which records and fields cross over, and in which direction, instead of maintaining pipeline code.

Common use cases

  • 01 Publish Hive aggregate tables to a faster serving database for dashboards.
  • 02 Bridge a legacy Hadoop warehouse to a cloud warehouse during migration by syncing tables continuously.
  • 03 Push hired candidates from an ATS into Paylocity via the Onboarding endpoint, then read Onboarding Status to confirm the record before the first payroll run.
  • 04 Upsert recurring Deductions and Earnings on employee records when benefits or 401(k) elections change in a benefits admin system, without re-keying payroll setup.

Common sync patterns

Headcount and cost joined with everything else

Analysts combine Paylocity's workforce records with finance, product, or operational data already in Apache Hive for reporting the HR system cannot produce on its own.

Fresh data instead of last night's load

Because changes stream continuously, reports query current workforce data rather than waiting for an overnight load window to finish.

Queryable history for planning and audit

A continuously synced copy in Apache Hive gives you a durable, queryable record of how Paylocity's records change over time, for headcount planning and audit questions.

What you can sync between Apache Hive and Paylocity

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 Paylocity objects How this pairing syncs
Databases Metastore namespaces that scope tables and grants. Pay Statements Read-only detailed payroll statement data — earnings, deductions, taxes, and direct deposit allocations by year, check date, or date range. Pulled for reporting, never written. Databases is specific to Apache Hive and Pay Statements to Paylocity — each maps to any object or custom field on the other side.
Managed Tables Tables whose data lifecycle Hive controls, used as warehouse destinations. Company Codes Read-only reference codes and descriptions (cost centers, departments, positions) used to validate field mappings on employee writes. Managed Tables is specific to Apache Hive and Company Codes to Paylocity — each maps to any object or custom field on the other side.
External Tables Tables over existing files in HDFS or object storage, read without moving data. Custom Fields Read-only company-specific custom fields returned by category, used to enrich the employee record downstream. External Tables is specific to Apache Hive and Custom Fields to Paylocity — each maps to any object or custom field on the other side.
Partitions Directory-mapped subsets (often by date) that bound incremental sync reads. Employees Core HR record keyed by companyId + employeeId; two-way via Create New Employee (POST) and Update Employee (PATCH), plus Get Employee / Get All Employees for reads. Partitions is specific to Apache Hive and Employees to Paylocity — each maps to any object or custom field on the other side.
Views Logical views readable as modeled sources. Onboarding Create Employee Onboarding pushes new-hire data into Paylocity's onboarding workflow; Get Onboarding Status reads back partner onboarding progress. Write-in for hires from an ATS. Views is specific to Apache Hive and Onboarding to Paylocity — each maps to any object or custom field on the other side.
Materialized Views Precomputed results available in newer Hive versions for faster reads. Deductions (Pay Setup) Recurring deduction codes at the employee level; two-way via Upsert Deduction and Delete, with Get Deduction / Get All Deductions for reads. Materialized Views is specific to Apache Hive and Deductions (Pay Setup) to Paylocity — each maps to any object or custom field on the other side.

How changes propagate between Apache Hive and Paylocity

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.

Apache Hive Paylocity Interval-based propagation

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 Paylocity through its API, with automatic retries and rate-limit backoff.

Paylocity Apache Hive Sub-second propagation

DetectionPaylocity notifies Stacksync of record changes through webhook events. Webhooks — Paylocity POSTs Employee New Hire, Employee Change, Termination, Payroll Processed, and Time Off Approval events to a callback URL.

DeliveryEach detected change is applied to Apache Hive as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Hive: No API quotas; query latency reflects the batch-oriented execution engine underneath.
  • Paylocity: 25 requests per second (1,500 per minute); exceeding it returns HTTP 429. Every path is scoped to a Paylocity-assigned companyId (a company code, not a UUID).
What ships with Apache Hive ⇄ Paylocity

Connect Apache Hive and Paylocity for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Hive–Paylocity connection.

Real-time

Two-way sync

Changes in Apache Hive or Paylocity instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Hive or Paylocity 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 Apache Hive or Paylocity record.

Observability

Monitoring

Track your Apache Hive ⇄ Paylocity sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Hive and Paylocity.

How the Apache Hive and Paylocity connectors work

Apache Hive

Integration surface
SQL (HiveQL) over JDBC/ODBC via HiveServer2 (Thrift)
Authentication
Deployment-dependent: Kerberos, LDAP, or username/password
Change detection
Polling on partition values or timestamp columns; no general-purpose change log for external consumers
Capabilities
read · write
Rate limits
No API quotas; query latency reflects the batch-oriented execution engine underneath

Paylocity

Integration surface
REST API (v1 and v2), JSON payloads
Authentication
OAuth 2.0 client credentials via the Paylocity Identity Provider (/IdentityServer/connect/token) with the WebLinkAPI scope; access tokens expire after one hour and API access must be enabled by Paylocity for the company
Change detection
Webhooks — Paylocity POSTs Employee New Hire, Employee Change, Termination, Payroll Processed, and Time Off Approval events to a callback URL; payloads carry only companyId and employeeId, so the receiver calls the relevant API to fetch changed values. Scheduled polling is used for objects without webhooks.
Capabilities
read · write · webhooks
Rate limits
25 requests per second (1,500 per minute); exceeding it returns HTTP 429. Every path is scoped to a Paylocity-assigned companyId (a company code, not a UUID).
How it works

How to connect Apache Hive to Paylocity — 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 Apache Hive and Paylocity 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
    Apache Hive connected
    Paylocity connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Hive and Paylocity 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 · Apache Hive ⇄ Paylocity
    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
    Apache Hive Paylocity
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Hive and Paylocity integration FAQ

SECURITY

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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.

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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 440 integrations available for Apache Hive and Paylocity.

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