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Data warehouse ⇄ CRM

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

Keep Apache Druid and Nimble in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

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

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Migrated from Mulesoft
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Migrated from Celigo
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Migrated from Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Apache Druid and Nimble

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

Common use cases

  • Push product usage or billing flags from internal databases into Nimble custom fields so reps have context before outreach.
  • Keep deals aligned between Nimble and an accounting system so invoicing starts when a deal closes.
  • Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
  • Expose product telemetry stored in Druid to business tools without granting direct cluster access.

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 Nimble 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 Nimble, where the people working accounts actually see them.

What you can sync between Apache Druid and Nimble

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 Nimble objects
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Custom fields Account-defined contact attributes that carry enrichment or internal identifiers
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Contacts Person records with multi-value fields for email, phone, and social profiles; the primary sync entity
Dimensions String and categorical columns used for filtering and grouping in synced queries. Companies Stored as contact records with a company record type, so they sync through the same contacts resource
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Deals Pipeline records linked to contacts, synced to keep revenue systems aligned with sales activity
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Tasks To-do items tied to contacts, mirrored into work-management tools or reporting tables
Lookups Key-value mappings joined at query time, refreshable from external systems. Activities Calls, events, and interaction history used for engagement reporting outside Nimble
What ships with Apache Druid ⇄ Nimble

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Nimble 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 Nimble record.

Observability

Monitoring

Track your Apache Druid ⇄ Nimble 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 Nimble.

How the Apache Druid and Nimble 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

Nimble

Integration surface
REST API (JSON)
Authentication
API key; OAuth 2.0 available for registered applications
Change detection
polling on record modification timestamps
Capabilities
read · write
Rate limits
subject to per-account API request quotas
How it works

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

    Choose tables

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

Apache Druid and Nimble integration FAQ

SECURITY

Security teams love 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.

SOC 2 type II
ISO 27001
HIPAA BAA
GDPR
CCPA
CSA STAR
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:

Related integrations

Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Druid and Nimble.

Popular · 8 of 386
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