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Data warehouse ⇄ CRM

Apache Druid to Chorusai integration — real-time, two-way sync

Keep Apache Druid 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.

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Why teams connect Apache Druid and Chorusai

Sync Chorusai into Apache Druid 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. Playlists, Engagements, Recordings (Conversations), Users from Chorusai land in Apache Druid as live tables, updated within seconds, and columns computed in Apache Druid write back to fields in Chorusai. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Upload externally recorded dialer or web-conference audio into Chorus as Recordings so it gets transcribed and analyzed like native calls.
  • 02 Sync Trackers such as pricing, competitor, and next-steps mentions onto matching CRM Opportunities as coaching and deal-risk signals.
  • 03 Expose product telemetry stored in Druid to business tools without granting direct cluster access.
  • 04 Query aggregated event metrics from Druid and sync them into CRM account fields for usage-based selling.

Common sync patterns

Cleanup that sticks

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

CRM analytics on live data

Accounts, contacts, and activity from Chorusai are queryable in Apache Druid moments after they change, so dashboards stop lagging the reality they describe.

Scores and segments back on the record

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

What you can sync between Apache Druid and Chorusai

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 Druid objects Chorusai objects How this pairing syncs
Tasks Batch ingestion and compaction jobs monitored during data loads. Users Chorus users with roles and team membership; read to map engagement owners and participants to CRM and warehouse identities. Tasks is specific to Apache Druid and Users to Chorusai — each maps to any object or custom field on the other side.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Trackers AI keyword and topic trackers (pricing, competitors, next steps) surfaced within a conversation; read out as coaching and deal-risk signals. Datasources is specific to Apache Druid and Trackers to Chorusai — each maps to any object or custom field on the other side.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Deals CRM opportunity context attached to a conversation (account, deal, owner); read to attribute call activity to open pipeline. Segments is specific to Apache Druid and Deals to Chorusai — each maps to any object or custom field on the other side.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Scorecards Call QA and coaching assessments with reviewer, recipient, and scores; read and exported for rep-performance reporting. Dimensions is specific to Apache Druid and Scorecards to Chorusai — each maps to any object or custom field on the other side.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Moments Timestamped highlight clips from a conversation; created via the API to capture key call snippets. Metrics is specific to Apache Druid and Moments to Chorusai — each maps to any object or custom field on the other side.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Playlists Curated collections of Moments and Recordings; created and managed to share coaching examples across teams. Ingestion Supervisors is specific to Apache Druid and Playlists to Chorusai — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid and Chorusai

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 Druid Chorusai Interval-based propagation

DetectionStacksync polls Apache Druid for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Druid through streaming or batch ingestion rather than row updates.

DeliveryEach detected change is written to Chorusai through its API, with automatic retries and rate-limit backoff.

Chorusai Apache Druid Interval-based propagation

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 applied to Apache Druid as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • Apache Druid: No fixed API quotas; query concurrency is bounded by broker and historical node capacity.
  • Chorusai: Rate limits are not publicly documented; recording upload and analysis are asynchronous, so transcripts and trackers appear only after processing_state completes.
What ships with Apache Druid ⇄ Chorusai

Connect Apache Druid and Chorusai for flexible, real-time data sync.

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Chorusai 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 Druid or Chorusai record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Apache Druid and Chorusai.

How the Apache Druid and Chorusai connectors work

Apache Druid

Integration surface
REST API (SQL over HTTP and native JSON queries); JDBC via Avatica
Authentication
Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy
Change detection
Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates
Capabilities
read · write
Rate limits
No fixed API quotas; query concurrency is bounded by broker and historical node capacity

Chorusai

Integration surface
REST API (api-docs.chorus.ai)
Authentication
Per-user API token generated in Chorus Personal Settings, sent in the Authorization request header
Change detection
Polling the engagements endpoint on date_time and processing_state; no public change webhooks or CDC
Capabilities
read · write
Rate limits
Rate limits are not publicly documented; recording upload and analysis are asynchronous, so transcripts and trackers appear only after processing_state completes
Chorusai setup guide
How it works

How to connect Apache Druid to Chorusai — 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 Druid 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.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Apache Druid connected
    Chorusai connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Apache Druid 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.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Apache Druid ⇄ Chorusai
    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 Druid Chorusai
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Apache Druid and Chorusai 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 461 integrations available for Apache Druid and Chorusai.

Popular · 7 of 461
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