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Data warehouse ⇄ CRM

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

Keep Apache Druid and Close 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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Why teams connect Apache Druid and Close

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

Common use cases

  • Keep Close contacts aligned with a marketing automation platform so outreach lists stay current.
  • Push call, SMS, and email activity data into a warehouse for rep performance and outreach-cadence analysis.
  • 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.

A single customer view

Join Close'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.

CRM analytics on live data

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

What you can sync between Apache Druid and Close

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 Close objects
Lookups Key-value mappings joined at query time, refreshable from external systems. Users Sales reps referenced as owners on leads, opportunities, and activities.
Tasks Batch ingestion and compaction jobs monitored during data loads. Smart Views Saved lead searches that can scope which records a segment-based sync pulls.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Leads The top-level record in Close; represents a company and holds its contacts, opportunities, and activity history.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Contacts People nested under a lead, with emails and phone numbers used for outreach syncs.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Opportunities Deal records with value, confidence, and status; commonly synced to reporting and billing systems.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Activities Calls, emails, SMS, notes, and meetings logged against a lead; the source for engagement analytics.
What ships with Apache Druid ⇄ Close

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Close 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 Close record.

Observability

Monitoring

Track your Apache Druid ⇄ Close 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 Close.

How the Apache Druid and Close 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

Close

Integration surface
REST API
Authentication
API key (sent via HTTP Basic auth)
Change detection
Webhook subscriptions for record events, with polling on date_updated fields for backfills
Capabilities
read · write · webhooks
Rate limits
Subject to per-endpoint rate limits communicated in response headers
How it works

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

    Choose tables

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

Apache Druid and Close 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.

Learn more about security
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:

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 386 integrations available for Apache Druid and Close.

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