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Data warehouse ⇄ CRM

Amazon Redshift to Xactly integration — real-time, two-way sync

Keep Amazon Redshift 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.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Amazon Redshift and Xactly

Sync Xactly into Amazon Redshift continuously and push warehouse results back onto CRM records, one two-way connection instead of two pipelines.

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. Participants (Payees), Positions & Titles, Quotas / Targets, Payment Summary (Payable) from Xactly land in Amazon Redshift as live tables, updated within seconds, and columns computed in Amazon Redshift 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 Push approved Payment Summary amounts from Incent into a payroll or accounts-payable system so payouts are paid from the mastered comp result.
  • 02 Replicate Products and Customer/Account master from CRM/ERP into Xactly so crediting rules resolve against consistent reference data.
  • 03 Centralize CRM, ERP, and product data in Redshift so analysts join it with warehouse tables.
  • 04 Publish finance rollups computed in Redshift back to spreadsheets or operational tools.

Common sync patterns

Scores and segments back on the record

Lead scores, churn risk, or usage segments computed in Amazon Redshift 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 Amazon Redshift to build the customer picture the CRM alone cannot hold.

Cleanup that sticks

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

What you can sync between Amazon Redshift 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.

Amazon Redshift objects Xactly objects How this pairing syncs
Stored Procedures SQL procedures sometimes invoked around load steps. 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. Stored Procedures is specific to Amazon Redshift and Participants (Payees) to Xactly — each maps to any object or custom field on the other side.
Users and Groups Principals used to grant a sync connection scoped access. Positions & Titles Org-hierarchy positions and titles that credits and quotas roll up to; loaded and maintained through Connect (write) and read to resolve the hierarchy, so read and write. Users and Groups is specific to Amazon Redshift and Positions & Titles to Xactly — each maps to any object or custom field on the other side.
Databases Top-level containers within a cluster or serverless workgroup. Quotas / Targets Period quota and target values per position or plan; loaded from planning tools through Connect (write) and read for attainment reporting, so read and write. Databases is specific to Amazon Redshift and Quotas / Targets to Xactly — each maps to any object or custom field on the other side.
Schemas Namespaces used to organize synced tables and control grants. Payment Summary (Payable) Approved payable amounts per participant per period; read as the output that feeds payroll and accounts payable, so effectively read-only. Schemas is specific to Amazon Redshift and Payment Summary (Payable) to Xactly — each maps to any object or custom field on the other side.
Tables Columnar tables used as sync destinations for SaaS and database data. 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. Tables is specific to Amazon Redshift and Products & Customers to Xactly — each maps to any object or custom field on the other side.
Views SQL views readable as modeled sources for reverse syncs. 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. Views is specific to Amazon Redshift and Orders to Xactly — each maps to any object or custom field on the other side.

How changes propagate between Amazon Redshift 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.

Amazon Redshift Xactly Interval-based propagation

DetectionStacksync polls Amazon Redshift for changes on an incremental schedule, reading only records changed since the previous pass. Polling or query-based diffing.

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

Xactly Amazon Redshift 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.

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

Rate-limit considerations

  • Amazon Redshift: Bounded by cluster or serverless capacity and concurrency settings rather than API quotas.
  • 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 Amazon Redshift ⇄ Xactly

Connect Amazon Redshift and Xactly for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Amazon Redshift 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 Amazon Redshift or Xactly record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Amazon Redshift and Xactly.

How the Amazon Redshift and Xactly connectors work

Amazon Redshift

Integration surface
SQL over JDBC/ODBC (PostgreSQL-derived protocol); Redshift Data API over HTTPS
Authentication
Database credentials or IAM-based authentication
Change detection
Polling or query-based diffing; Redshift does not expose a transaction log for external CDC consumers
Capabilities
read · write
Rate limits
Bounded by cluster or serverless capacity and concurrency settings rather than API quotas

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 Amazon Redshift 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 Amazon Redshift 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
    Amazon Redshift connected
    Xactly connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Amazon Redshift 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 · Amazon Redshift ⇄ 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
    Amazon Redshift Xactly
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Amazon Redshift 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.

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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 565 integrations available for Amazon Redshift and Xactly.

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