Real-time
Two-way sync
Changes in Apache Druid or Front instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Business productivity
Apache Druid to Front integration — real-time, two-way sync
Keep Apache Druid and Front 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 Matillion
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Migrated from Fivetran
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Migrated from Celigo
Why teams connect Apache Druid and Front
Get the data locked inside Front into Apache Druid as live tables, and send results back where Front can use them, without writing a pipeline.
Whatever Front is used for, it accumulates data the rest of the company wants to analyze, and that data usually sits behind an API rather than in the warehouse. Building and babysitting an extraction pipeline is the tax most teams pay for it.
Stacksync syncs Contacts, Accounts, Inboxes, Tags from Front into tables in Apache Druid continuously, handling schema, rate limits, and retries. Because the sync is bi-directional, results computed in Apache Druid can also be written back into fields in Front where the tool can use them.
Common use cases
- Sync conversations, messages, and tags into Postgres for response-time and volume analytics across inboxes.
- Write CRM account tier, owner, and renewal data into Front contact and account custom fields so it shows next to the conversation.
- Sync Druid query results into a warehouse to combine real-time aggregates with historical models.
- Keep lookup tables in Druid refreshed from a CRM or database so query-time joins use current reference data.
Where Front accepts updates: operational write-back
Segments, scores, or reference values computed in Apache Druid sync back onto records in Front, putting analysis where the work happens.
History that outlives the tool
A continuously synced copy in Apache Druid preserves a queryable record even as data ages out of Front or gets changed inside it.
Analytics on Front's data
Records and events from Front land in Apache Druid as queryable tables, current within seconds and ready to join with the rest of the warehouse.
What you can sync between Apache Druid and Front
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 | Front objects | |
|---|---|---|
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Inboxes Shared queues that conversations live in; used to segment reporting by team or channel. | |
| Lookups Key-value mappings joined at query time, refreshable from external systems. | Tags Labels applied to conversations; drive routing and category-level analytics. | |
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Teammates Agents; used for ownership mapping and workload reporting. | |
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Channels Connected addresses (email, SMS, chat); define where messages originate and send from. | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | Conversations The central threaded unit that messages, comments, and tags attach to; synced for support analytics. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Messages Inbound and outbound emails, chats, and SMS within a conversation; read out for response-time reporting. |
What ships with Apache Druid ⇄ Front
Connect Apache Druid and Front for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Front connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever Apache Druid or Front 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 Front record.
Observability
Monitoring
Track your Apache Druid ⇄ Front 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 Front.
How the Apache Druid and Front 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
Front
- Integration surface
- REST API (Core API)
- Authentication
- OAuth authorization via the Stacksync UI ("Connections" > "create new connection" > "Front" > "Authorize") — no coding required
- Change detection
- Application webhooks and rule-triggered webhooks, with the events endpoint available for polling
- Capabilities
- read · write · webhooks
- Rate limits
- Request limits vary by plan.
How it works
How to connect Apache Druid to Front — 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 Front 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
Front
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the Apache Druid and Front 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 ⇄ FrontCustomers 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 FrontCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
Apache Druid and Front integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between Apache Druid and Front: authenticate both systems, choose the objects to sync (such as Apache Druid's Ingestion Supervisors and Lookups), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Yes — Stacksync ships production-grade connectors for both Apache Druid and Front. 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 Front: Application webhooks and rule-triggered webhooks, with the events endpoint available for polling. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
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On the Front side: Contacts, Accounts, Inboxes, Tags, plus custom fields where Front exposes them. On the Apache Druid side: Dimensions, Metrics, Ingestion Supervisors, Lookups. Stacksync auto-detects both schemas and converts types between the two systems.
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Yes. Each object mapping can be bidirectional or restricted to a single direction (both systems accept writes). Read-only mirrors, one-way pushes, and full two-way sync can be mixed in the same integration.
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Common patterns for Apache Druid and Front: Where Front accepts updates: operational write-back; History that outlives the tool; Analytics on Front's data. Segments, scores, or reference values computed in Apache Druid sync back onto records in Front, putting analysis where the work happens.
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 Front.
Popular · 8 of 386
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Apache Druid ⇄ GitHub -
Apache Druid ⇄ Atlassian -
Apache Druid ⇄ Braze -
Apache Druid ⇄ ConnectWise -
Front ⇄ Cloudera Data Platform -
Front ⇄ Dremio -
Front ⇄ Exasol -
Front ⇄ Firebolt
No integrations match .
