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Data warehouse ⇄ Database

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

Keep Apache Druid and Supabase 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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Why teams connect Apache Druid and Supabase

Connect Supabase and Apache Druid with one live, two-way sync: operational rows flow into the warehouse, and computed results flow back where systems can read them fast.

Operational databases and analytical warehouses want the same data at different moments. Analysts want Supabase's rows in Apache Druid, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Supabase where the services that read from it get them at normal query latency.

Stacksync covers both directions with one connection. Tables or collections in Supabase sync into Apache Druid in real time, and result tables in Apache Druid sync back into Supabase, with schema and type mapping between the two systems handled for you.

Common use cases

  • 01 Query aggregated event metrics from Druid and sync them into CRM account fields for usage-based selling.
  • 02 Feed operational records into Druid via batch ingestion so analysts get interactive slice-and-dice on fresh data.
  • 03 Sync application tables in Supabase with the CRM two-way so new signups appear as contacts and sales edits flow back to the app
  • 04 Mirror billing and subscription records into Supabase tables the application can join directly

Common sync patterns

Fresh analytics without loading windows

Because changes stream continuously, analysts query current data instead of waiting for last night's load.

Offload heavy reads

Point analytical queries at the synced copy in Apache Druid and keep Supabase focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Supabase land in Apache Druid as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between Apache Druid and Supabase

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 Supabase objects How this pairing syncs
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Row Level Security Policies Row-level access rules that govern what the REST layer exposes. Ingestion Supervisors is specific to Apache Druid and Row Level Security Policies to Supabase — each maps to any object or custom field on the other side.
Lookups Key-value mappings joined at query time, refreshable from external systems. JSONB Columns Semi-structured payloads such as event properties or nested objects. Lookups is specific to Apache Druid and JSONB Columns to Supabase — each maps to any object or custom field on the other side.
Tasks Batch ingestion and compaction jobs monitored during data loads. Database Functions Postgres functions that can transform or validate synced rows. Tasks is specific to Apache Druid and Database Functions to Supabase — 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. Storage Object Metadata File metadata rows that can be joined to synced application data. Datasources is specific to Apache Druid and Storage Object Metadata to Supabase — each maps to any object or custom field on the other side.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Tables Standard Postgres tables; the primary two-way sync target. Segments is specific to Apache Druid and Tables to Supabase — 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. Views Read-side projections exposed to outbound syncs. Dimensions is specific to Apache Druid and Views to Supabase — each maps to any object or custom field on the other side.

How changes propagate between Apache Druid and Supabase

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 Supabase 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 applied to Supabase as a row-level write, with types converted between the two schemas.

Supabase Apache Druid Sub-second propagation

DetectionSupabase pushes changes as they happen — webhook events backed by change data capture. Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime.

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.
  • Supabase: SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits.
What ships with Apache Druid ⇄ Supabase

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Supabase 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 Supabase record.

Observability

Monitoring

Track your Apache Druid ⇄ Supabase 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 Supabase.

How the Apache Druid and Supabase 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

Supabase

Integration surface
Direct PostgreSQL wire protocol connection, plus an auto-generated REST API (PostgREST)
Authentication
Database credentials (connection string) for SQL access; API keys (anon / service role) for the REST layer
Change detection
Log-based CDC via Postgres logical replication, the same WAL feed that powers Supabase Realtime; database webhooks can also fire on row changes
Capabilities
read · write · CDC · webhooks
Rate limits
SQL access is bounded by connection limits (pooled connections are provided); the REST layer is subject to the platform's limits
How it works

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

    Choose tables

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

Apache Druid and Supabase 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 474 integrations available for Apache Druid and Supabase.

Popular · 7 of 474
All Apache Druid integrations All Supabase integrations Browse all integrations
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