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Data warehouse ⇄ Database

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

Keep Apache Druid and SingleStore 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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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Apache Druid and SingleStore

Connect SingleStore 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 SingleStore'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 SingleStore where the services that read from it get them at normal query latency.

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

Common use cases

  • 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.
  • Feed synced operational data into applications that need low-latency responses over fresh data.
  • Mirror CRM and SaaS objects into SingleStore tables to serve low-latency operational dashboards.

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

Aggregates or model outputs computed in Apache Druid sync into SingleStore, where whatever reads from that database gets them without querying the warehouse.

Fresh analytics without loading windows

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

What you can sync between Apache Druid and SingleStore

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 SingleStore objects
Lookups Key-value mappings joined at query time, refreshable from external systems. Indexes and Shard Keys Determine data distribution and lookup speed for sync match keys.
Tasks Batch ingestion and compaction jobs monitored during data loads. Databases The connection target containing the tables a sync addresses.
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Tables (rowstore and columnstore) Primary read/write target; storage type affects whether a table suits point lookups or scans.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Views Read-only projections used as curated sync sources.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Reference Tables Small tables replicated to every node, often used for dimension data in syncs.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Pipelines Native ingestion jobs from Kafka or object storage that coexist with external syncs.
What ships with Apache Druid ⇄ SingleStore

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or SingleStore 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 SingleStore record.

Observability

Monitoring

Track your Apache Druid ⇄ SingleStore 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 SingleStore.

How the Apache Druid and SingleStore 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

SingleStore

Integration surface
SQL over the MySQL wire protocol; an HTTP Data API is also available for SQL over REST
Authentication
Database credentials
Change detection
Polling on timestamp or watermark columns; the platform also provides change-observation features in recent versions
Capabilities
read · write
Rate limits
No API rate limits; throughput is bounded by workspace or cluster size
How it works

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

    Choose tables

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

Apache Druid and SingleStore 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 SingleStore.

Popular · 8 of 386
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