Real-time
Two-way sync
Changes in Apache Druid or Kustomer instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ CRM
Apache Druid to Kustomer integration — real-time, two-way sync
Keep Apache Druid and Kustomer 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
Case study
Migrated from MuleSoft
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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 Kustomer
Sync Kustomer 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. Conversations, Messages, Companies, Custom Objects (Klasses) from Kustomer land in Apache Druid as live tables, updated within seconds, and columns computed in Apache Druid write back to fields in Kustomer. There is no separate ETL and reverse-ETL stack to stitch together and no jobs to babysit.
Common use cases
- 01 Keep customer attributes updated from billing systems so routing rules and SLAs reflect account value
- 02 Escalate conversation-derived signals into the CRM as tasks or opportunities
- 03 Feed operational records into Druid via batch ingestion so analysts get interactive slice-and-dice on fresh data.
- 04 Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
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 Kustomer, where the people working accounts actually see them.
A single customer view
Join Kustomer'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 Kustomer
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 | Kustomer objects | How this pairing syncs | |
|---|---|---|---|
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Customers The central record whose timeline aggregates every interaction; external attributes sync onto it. | Tasks is specific to Apache Druid and Customers to Kustomer — 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. | Conversations Support threads across channels sync outward for analytics and CRM context. | Datasources is specific to Apache Druid and Conversations to Kustomer — each maps to any object or custom field on the other side. | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | Messages Individual messages within conversations support full-thread replication. | Segments is specific to Apache Druid and Messages to Kustomer — 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. | Companies Organization records group customers and map to CRM accounts. | Dimensions is specific to Apache Druid and Companies to Kustomer — each maps to any object or custom field on the other side. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | Custom Objects (Klasses) Structured external records such as orders and subscriptions synced in to appear on the customer timeline. | Metrics is specific to Apache Druid and Custom Objects (Klasses) to Kustomer — 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. | Users Agent records map conversation ownership to people in other systems. | Ingestion Supervisors is specific to Apache Druid and Users to Kustomer — each maps to any object or custom field on the other side. |
How changes propagate between Apache Druid and Kustomer
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 Kustomer 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 Kustomer through its API, with automatic retries and rate-limit backoff.
Kustomer Apache Druid Sub-second propagation
DetectionKustomer notifies Stacksync of record changes through webhook events. Outbound webhooks on record 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.
- Kustomer: Subject to the platform's API rate limits.
What ships with Apache Druid ⇄ Kustomer
Connect Apache Druid and Kustomer for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Kustomer connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Druid or Kustomer 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 Kustomer record.
Observability
Monitoring
Track your Apache Druid ⇄ Kustomer 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 Kustomer.
How the Apache Druid and Kustomer 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
Kustomer
- Integration surface
- REST API
- Authentication
- API key used as a bearer token, scoped by role
- Change detection
- Outbound webhooks on record events, plus polling for backfill
- Capabilities
- read · write · webhooks
- Rate limits
- Subject to the platform's API rate limits
How it works
How to connect Apache Druid to Kustomer — 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.
- 01
Connect your apps
Authenticate Apache Druid and Kustomer with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Apache Druid
connected
Kustomer
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Druid and Kustomer 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.
objects · Apache Druid ⇄ KustomerCustomers 12,480Sales Orders 8,213Invoices 5,902Items 1,344 - 03
Map fields
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Apache Druid KustomerCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Druid and Kustomer integration FAQ
-
Yes. Stacksync provides a managed, real-time two-way integration between Apache Druid and Kustomer: authenticate both systems, choose the objects to sync (such as Apache Druid's Tasks and Datasources), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Kustomer: Custom object types are called Klasses, and they are the standard mechanism for landing external data like orders and subscriptions where agents work. Apache Druid: It exposes both a SQL API over HTTP and a native JSON query language, with SQL translated onto native queries. Stacksync's field mapping accounts for these differences between Apache Druid and Kustomer without custom code.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Druid and Kustomer records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Druid and Kustomer connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Druid–Kustomer integration in-house.
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Yes — Stacksync ships production-grade connectors for both Apache Druid and Kustomer. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
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Change detection on Apache Druid: Not applicable for reads out (polling by time interval); data enters Druid through streaming or batch ingestion rather than row updates. On Kustomer: Outbound webhooks on record events, plus polling for backfill. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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.
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:
Related integrations
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