Skip to content
Data warehouse ⇄ CRM

Apache Kylin to Xactly integration — real-time data sync

Keep Apache Kylin and Xactly 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
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Apache Kylin and Xactly

Flow Apache Kylin data into Xactly in real time — no exports, no schedulers, no custom scripts.

Apache Kylin is a read-only source: Stacksync reads its data in real time and delivers it into Xactly, so Xactly always reflects the current state of Apache Kylin — without exports, scripts, or schedulers.

The CRM feeds the warehouse and the warehouse should feed the CRM: relationship data flows one way, and computed scores, segments, and customer context flow back. Most teams build the first half as a batch pipeline and never quite get to the second.

Stacksync does both with one connection. Quotas / Targets, Payment Summary (Payable), Products & Customers, Orders from Xactly land in Apache Kylin as live tables, updated within seconds, and columns computed in Apache Kylin write back to fields in Xactly. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Replicate Products and Customer/Account master from CRM/ERP into Xactly so crediting rules resolve against consistent reference data.
  • 02 Mirror commission Transactions and Credits into a data warehouse to power rep-facing dashboards and comp-plan analytics without manual exports.
  • 03 Trigger downstream syncs after segment build jobs complete so consumers only read refreshed data.
  • 04 Read pre-aggregated metrics from Kylin and sync them into CRM fields or planning spreadsheets on a schedule.

Common sync patterns

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Apache Kylin appear as fields in Xactly, where the people working accounts actually see them.

A single customer view

Join Xactly's relationship data with billing, product, and support data in Apache Kylin to build the customer picture the CRM alone cannot hold.

Cleanup that sticks

Deduplication and normalization done in Apache Kylin can be written back, so warehouse-side cleanup actually fixes the CRM.

What you can sync between Apache Kylin and Xactly

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 Kylin objects Xactly objects How this pairing syncs
Cubes / Indexes Pre-computed aggregate structures that answer queries at low latency. Payment Summary (Payable) Approved payable amounts per participant per period; read as the output that feeds payroll and accounts payable, so effectively read-only. Cubes / Indexes is specific to Apache Kylin and Payment Summary (Payable) to Xactly — each maps to any object or custom field on the other side.
Source Tables Hive or other upstream tables that builds read from. Products & Customers Product and customer/account master used in crediting rules and reporting; loaded and updated from CRM/ERP through Connect (write) and read for lookups, so read and write. Source Tables is specific to Apache Kylin and Products & Customers to Xactly — each maps to any object or custom field on the other side.
Segments Time-ranged build units that partition pre-computed data. Orders Sales order and transaction records loaded into Incent as the raw input for crediting and calculation; created and updated through Connect load and ETL steps (write) and read back for reconciliation, so read and write. Segments is specific to Apache Kylin and Orders to Xactly — each maps to any object or custom field on the other side.
Build Jobs Batch jobs that compute or refresh segments, monitored via the REST API. Credits Crediting records that tie an order to a participant and position; system-calculated credits are read, while manual and adjustment credits are loaded through Connect, so read and write. Build Jobs is specific to Apache Kylin and Credits to Xactly — each maps to any object or custom field on the other side.
Projects Top-level workspaces that group models, tables, and jobs. Transactions (Commission & Bonus) Calculated commission and bonus line items produced by Incent's calculation engine; read as the output of comp runs for reporting and downstream payout, so effectively read-only results. Projects is specific to Apache Kylin and Transactions (Commission & Bonus) to Xactly — each maps to any object or custom field on the other side.
Models Star-schema definitions over source tables that determine what can be queried. Participants (Payees) Sales reps and payees keyed to positions; loaded and updated from HRIS/HCM source data through Connect (write) and read for roster reporting, so read and write. Models is specific to Apache Kylin and Participants (Payees) to Xactly — each maps to any object or custom field on the other side.

How changes propagate between Apache Kylin and Xactly

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 Kylin Xactly Interval-based propagation

DetectionStacksync polls Apache Kylin for changes on an incremental schedule, reading only records changed since the previous pass. Data freshness follows segment build and refresh jobs, so integrations poll query results.

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

Xactly Apache Kylin Interval-based propagation

DetectionStacksync polls Xactly for changes on an incremental schedule, reading only records changed since the previous pass. No CDC log for external tools to consume.

DeliveryApache Kylin does not accept inbound record writes, so this direction carries requests rather than records: Apache Kylin's output flows back as field updates on the originating Xactly records.

Rate-limit considerations

  • Apache Kylin: No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage.
  • Xactly: Xactly does not publish numeric per-second rate limits. The Connect platform enforces query concurrency and long-running-query limits, so large extracts are paged and heavy loads/queries run as asynchronous Connect jobs (submit, then retrieve results) rather than row-by-row calls; batch loads are the supported path for high volume.
What ships with Apache Kylin ⇄ Xactly

Connect Apache Kylin and Xactly for flexible, real-time data sync.

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Kylin or Xactly 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 Kylin or Xactly record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Kylin and Xactly.

How the Apache Kylin and Xactly connectors work

Apache Kylin

Integration surface
SQL over JDBC/ODBC plus a REST API for queries and administration
Authentication
Username/password (HTTP basic authentication on the REST API)
Change detection
Not applicable for row-level capture; data freshness follows segment build and refresh jobs, so integrations poll query results
Capabilities
read
Rate limits
No fixed API quotas; query capacity depends on the deployment and pre-computed index coverage

Xactly

Integration surface
Xactly Connect REST API v2 (JSON), plus ODBC/JDBC drivers over the same ANSI-SQL data model. Incent data is exposed as SQL-queryable objects (for example xactly_order, xactly_credit, xactly_transaction, xactly_payment); data is loaded and extracted through Connect load/query steps and server-side ETL Pipelines. The base host is region/pod-specific (for example https://<pod>.xactlycorp.com).
Authentication
OAuth 2.0 via the Xactly Connect API Gateway (bearer tokens issued on behalf of an Xactly Incent user), with HTTP Basic authentication using a dedicated Xactly Connect service-user's credentials also supported for the Connect REST API v2. The connecting user needs Connect/API access plus the relevant object permissions in Incent.
Change detection
No CDC log for external tools to consume. Incremental sync uses SQL predicates on modified/last-updated timestamp columns (for example WHERE modified_date > watermark) against Connect's queryable objects, or scheduled Connect ETL Pipelines that pull deltas since the last run. Xactly Connect has no outbound HTTP webhooks, so change detection is pull/ETL-based.
Capabilities
read · write
Rate limits
Xactly does not publish numeric per-second rate limits. The Connect platform enforces query concurrency and long-running-query limits, so large extracts are paged and heavy loads/queries run as asynchronous Connect jobs (submit, then retrieve results) rather than row-by-row calls; batch loads are the supported path for high volume.
Xactly setup guide
How it works

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

    Choose tables

    Pick the Apache Kylin and Xactly 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 Kylin ⇄ Xactly
    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 Kylin Xactly
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Apache Kylin and Xactly 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.

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

Every pair below is a real-time, two-way sync. Search all 415 integrations available for Apache Kylin and Xactly.

Popular · 4 of 415
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.