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Data warehouse ⇄ Database

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

Keep Apache Druid and Dynamo DB 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 Dynamo DB

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

Stacksync covers both directions with one connection. Tables or collections in Dynamo DB sync into Apache Druid in real time, and result tables in Apache Druid sync back into Dynamo DB, 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.
  • Replace ad-hoc export scripts with continuous sync driven by DynamoDB Streams.
  • Stream item changes from DynamoDB application tables into a Postgres or warehouse copy for SQL analytics.

Serve warehouse results at database speed

Aggregates or model outputs computed in Apache Druid sync into Dynamo DB, 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.

Offload heavy reads

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

What you can sync between Apache Druid and Dynamo DB

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 Dynamo DB objects
Datasources The table-like unit of storage and querying, the main target of reads and ingestion. Tables The top-level containers a sync targets; each table is addressed independently.
Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. Items Schemaless records keyed by partition (and optional sort) key, mapped to rows or SaaS objects in syncs.
Dimensions String and categorical columns used for filtering and grouping in synced queries. Attributes Per-item fields, including nested maps and lists, flattened or mapped during sync.
Metrics Numeric columns, often pre-aggregated at ingestion via rollup. Partition and Sort Keys The primary key pair used as the match key for bi-directional sync.
Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. Global Secondary Indexes Alternate access paths used when sync queries filter on non-key attributes.
Lookups Key-value mappings joined at query time, refreshable from external systems. DynamoDB Streams Ordered item-level change records consumed for incremental sync.
What ships with Apache Druid ⇄ Dynamo DB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Apache Druid or Dynamo DB 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 Dynamo DB record.

Observability

Monitoring

Track your Apache Druid ⇄ Dynamo DB 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 Dynamo DB.

How the Apache Druid and Dynamo DB 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

Dynamo DB

Integration surface
Proprietary JSON-over-HTTPS API accessed through AWS SDKs; PartiQL supported for SQL-like queries
Authentication
AWS IAM credentials with SigV4 request signing
Change detection
Item-level change streams via DynamoDB Streams or Kinesis Data Streams integration
Capabilities
read · write · CDC
Rate limits
Throughput is governed by the table's provisioned or on-demand capacity mode
How it works

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

    Choose tables

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

Apache Druid and Dynamo DB 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 Dynamo DB.

Popular · 8 of 386
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