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Database ⇄ CRM

Apache Cassandra to Xactly integration — real-time, two-way sync

Keep Apache Cassandra 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 Apache Cassandra and Xactly

Treat Xactly like part of your database: its records live in Apache Cassandra as real tables, and writes in either place sync to the other in seconds.

Product and engineering teams constantly need CRM data, and the CRM API is a poor way to get it: rate limits, pagination, custom objects, and integration code that breaks when an admin renames a field. What they actually want is the data in Apache Cassandra, where it can be queried and joined like everything else.

Stacksync mirrors Payment Summary (Payable), Products & Customers, Orders, Credits from Xactly into Keyspaces, Tables, Partitions and Rows, Materialized Views in Apache Cassandra with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Xactly with validation intact. Go-to-market teams keep working in the CRM, engineers keep working in the database, and neither has to think about the other.

Common use cases

  • 01 Mirror commission Transactions and Credits into a data warehouse to power rep-facing dashboards and comp-plan analytics without manual exports.
  • 02 Sync Participants, Positions, Titles, and Quotas from an HRIS/HCM and planning tools into Xactly so the org hierarchy and targets stay aligned with headcount changes.
  • 03 Write attributes computed elsewhere (scores, preferences) back into Cassandra tables serving low-latency reads.
  • 04 Feed Cassandra change streams into search indexes or caches that must track the source of truth.

Common sync patterns

Query the CRM like a database

Accounts, contacts, and custom objects from Xactly become tables in Apache Cassandra you can join with application data directly.

Product events onto CRM records

Signup, usage, or lifecycle changes written to Apache Cassandra sync onto the matching records in Xactly, giving go-to-market teams live product context.

Internal tools without API code

Back-office apps read and write the synced tables; Stacksync handles the Xactly API, limits, and retries.

What you can sync between Apache Cassandra 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 Cassandra objects Xactly objects How this pairing syncs
Secondary Indexes Optional indexes that allow filtered reads outside the partition key. Payment Summary (Payable) Approved payable amounts per participant per period; read as the output that feeds payroll and accounts payable, so effectively read-only. Secondary Indexes is specific to Apache Cassandra and Payment Summary (Payable) to Xactly — each maps to any object or custom field on the other side.
User-Defined Types Composite column types that syncs must flatten or map to structured fields. 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. User-Defined Types is specific to Apache Cassandra and Products & Customers to Xactly — each maps to any object or custom field on the other side.
Collections List, set, and map columns handled with type-aware field mapping. 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. Collections is specific to Apache Cassandra and Orders to Xactly — each maps to any object or custom field on the other side.
Counters Increment-only counter columns, usually read-only in syncs. 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. Counters is specific to Apache Cassandra and Credits to Xactly — each maps to any object or custom field on the other side.
Keyspaces Top-level namespaces with replication settings that scope a sync connection. 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. Keyspaces is specific to Apache Cassandra and Transactions (Commission & Bonus) to Xactly — each maps to any object or custom field on the other side.
Tables Wide-column tables addressed by partition key, the unit of row-level sync. 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. Tables is specific to Apache Cassandra and Participants (Payees) to Xactly — each maps to any object or custom field on the other side.

How changes propagate between Apache Cassandra 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 Cassandra Xactly Sub-second propagation

DetectionChanges in Apache Cassandra are captured at the source via change data capture — no polling loop against its API. Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns.

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

Xactly Apache Cassandra 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 written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.

Rate-limit considerations

  • Apache Cassandra: No API quotas; throughput is governed by cluster capacity and consistency-level choices.
  • 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 Cassandra ⇄ Xactly

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Cassandra 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 Cassandra or Xactly record.

Observability

Monitoring

Track your Apache Cassandra ⇄ 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 Cassandra and Xactly.

How the Apache Cassandra and Xactly connectors work

Apache Cassandra

Integration surface
CQL over the Cassandra native binary protocol
Authentication
Database credentials (password authenticator); TLS and role-based grants where configured
Change detection
Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns
Capabilities
read · write · CDC
Rate limits
No API quotas; throughput is governed by cluster capacity and consistency-level choices

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

    Choose tables

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

Apache Cassandra 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 453 integrations available for Apache Cassandra and Xactly.

Popular · 5 of 453
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