Two-way sync
Changes in Apache Cassandra or Chorusai instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Cassandra and Chorusai in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
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 Playlists, Engagements, Recordings (Conversations), Users from Chorusai into User-Defined Types, Collections, Counters, Keyspaces in Apache Cassandra with real-time, bi-directional sync. Read CRM records with plain queries; write updates from your application and they appear in Chorusai 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.
Back-office apps read and write the synced tables; Stacksync handles the Chorusai API, limits, and retries.
Field and stage updates in Chorusai arrive as row changes in Apache Cassandra, ready to drive jobs and notifications.
Accounts, contacts, and custom objects from Chorusai become tables in Apache Cassandra you can join with application data directly.
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 | Chorusai objects | How this pairing syncs | |
|---|---|---|---|
| Tables Wide-column tables addressed by partition key, the unit of row-level sync. | Deals CRM opportunity context attached to a conversation (account, deal, owner); read to attribute call activity to open pipeline. | Tables is specific to Apache Cassandra and Deals to Chorusai — each maps to any object or custom field on the other side. | |
| Partitions and Rows Records located by partition and clustering keys during reads and upserts. | Scorecards Call QA and coaching assessments with reviewer, recipient, and scores; read and exported for rep-performance reporting. | Partitions and Rows is specific to Apache Cassandra and Scorecards to Chorusai — each maps to any object or custom field on the other side. | |
| Materialized Views Server-maintained denormalized views; considered experimental and disabled by default in recent releases. | Moments Timestamped highlight clips from a conversation; created via the API to capture key call snippets. | Materialized Views is specific to Apache Cassandra and Moments to Chorusai — each maps to any object or custom field on the other side. | |
| Secondary Indexes Optional indexes that allow filtered reads outside the partition key. | Playlists Curated collections of Moments and Recordings; created and managed to share coaching examples across teams. | Secondary Indexes is specific to Apache Cassandra and Playlists to Chorusai — 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. | Engagements Meetings and dialer calls, the core record; filterable by date_time, participants, and processing_state, and polled incrementally to read conversation activity out. | User-Defined Types is specific to Apache Cassandra and Engagements to Chorusai — each maps to any object or custom field on the other side. | |
| Collections List, set, and map columns handled with type-aware field mapping. | Recordings (Conversations) The recorded call with utterances, transcript, thumbnails, and metrics; read for analysis and uploaded or deleted through the API. | Collections is specific to Apache Cassandra and Recordings (Conversations) to Chorusai — 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.
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 written to Chorusai through its API, with automatic retries and rate-limit backoff.
DetectionStacksync polls Chorusai for changes on an incremental schedule, reading only records changed since the previous pass. Polling the engagements endpoint on date_time and processing_state.
DeliveryEach detected change is written to Apache Cassandra through its API, with automatic retries and rate-limit backoff.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Cassandra–Chorusai connection.
Changes in Apache Cassandra or Chorusai instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Cassandra or Chorusai 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 Cassandra or Chorusai record.
Track your Apache Cassandra ⇄ Chorusai sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Cassandra and Chorusai.
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 Cassandra and Chorusai 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 Cassandra and Chorusai 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 Cassandra and Chorusai: authenticate both systems, choose the objects to sync (such as Apache Cassandra's Tables and Partitions and Rows), map fields visually, and changes propagate both ways in milliseconds — no code required.
Change detection on Apache Cassandra: Commit-log based CDC on tables with CDC enabled, or polling using writetime metadata and timestamp columns. On Chorusai: Polling the engagements endpoint on date_time and processing_state; no public change webhooks or CDC. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Chorusai side: Playlists, Engagements, Recordings (Conversations), Users, plus custom fields where Chorusai exposes them. On the Apache Cassandra side: User-Defined Types, Collections, Counters, Keyspaces. 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 Cassandra and Chorusai: Internal tools without API code; Trigger workflows from CRM changes; Query the CRM like a database. Back-office apps read and write the synced tables; Stacksync handles the Chorusai API, limits, and retries.
Apache Cassandra: CQL over the Cassandra native binary protocol. Authentication: Database credentials (password authenticator); TLS and role-based grants where configured. Chorusai: REST API (api-docs.chorus.ai). Authentication: Per-user API token generated in Chorus Personal Settings, sent in the Authorization request header. 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.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 451 integrations available for Apache Cassandra and Chorusai.