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Data warehouse ⇄ CRM

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

Keep Apache Druid and Kommo 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 Druid and Kommo

Sync Kommo 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. Contacts, Companies, Pipelines & Statuses, Tasks from Kommo land in Apache Druid as live tables, updated within seconds, and columns computed in Apache Druid write back to fields in Kommo. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.

Common use cases

  • 01 Route leads that originate in WhatsApp or Instagram conversations into other systems of record
  • 02 Replicate Kommo leads and contacts into a database or warehouse for reporting beyond built-in dashboards
  • 03 Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
  • 04 Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.

Common sync patterns

Scores and segments back on the record

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

A single customer view

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

Cleanup that sticks

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

What you can sync between Apache Druid and Kommo

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 Kommo objects How this pairing syncs
Tasks Batch ingestion and compaction jobs monitored during data loads. Tasks Follow-up records keep rep activity consistent across systems. Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Contacts Person records sync with other CRMs and databases for a shared contact file. Datasources is specific to Apache Druid and Contacts to Kommo — each maps to any object or custom field on the other side.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Companies Organization records map to accounts in ERPs and invoicing tools. Segments is specific to Apache Druid and Companies to Kommo — 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. Pipelines & Statuses Stage definitions structure lead progress and drive stage-change syncs to reporting tools. Dimensions is specific to Apache Druid and Pipelines & Statuses to Kommo — each maps to any object or custom field on the other side.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Notes Free-text and system notes attach context to synced leads and contacts. Metrics is specific to Apache Druid and Notes to Kommo — 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. Custom Fields Per-entity custom fields hold data written from external databases and enrichment. Ingestion Supervisors is specific to Apache Druid and Custom Fields to Kommo — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid and Kommo

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 Kommo 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 Kommo through its API, with automatic retries and rate-limit backoff.

Kommo Apache Druid Sub-second propagation

DetectionKommo notifies Stacksync of record changes through webhook events. Webhooks on record add and update events, plus polling for backfill.

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.
  • Kommo: Subject to per-account request rate limits.
What ships with Apache Druid ⇄ Kommo

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Kommo 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 Kommo record.

Observability

Monitoring

Track your Apache Druid ⇄ Kommo 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 Kommo.

How the Apache Druid and Kommo 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

Kommo

Integration surface
REST API
Authentication
OAuth 2.0 with refresh tokens
Change detection
Webhooks on record add and update events, plus polling for backfill
Capabilities
read · write · webhooks
Rate limits
Subject to per-account request rate limits
How it works

How to connect Apache Druid to Kommo — 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 Kommo 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
    Kommo connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

Apache Druid and Kommo 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.

Learn more about security
SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
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:

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 452 integrations available for Apache Druid and Kommo.

Popular · 6 of 452
All Apache Druid integrations All Kommo integrations Browse all integrations
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