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Database ⇄ Data warehouse

Elasticsearch to MotherDuck integration — real-time, two-way sync

Keep Elasticsearch and MotherDuck 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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  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Elasticsearch and MotherDuck

Connect Elasticsearch and MotherDuck 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 Elasticsearch's rows in MotherDuck, 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 Elasticsearch where the services that read from it get them at normal query latency.

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

Common use cases

  • Sync modeled MotherDuck tables outward to operational tools for activation
  • Share curated, synced datasets with other teams through read-only database shares
  • Sync CRM accounts and contacts into an Elasticsearch index to power internal search across customer records.
  • Push product catalog data from an ERP or commerce database into Elasticsearch for storefront search.

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 MotherDuck and keep Elasticsearch focused on its operational workload.

Operational data in the warehouse, minus the pipeline

Rows from Elasticsearch land in MotherDuck as they change, replacing hand-built CDC and batch extract jobs.

What you can sync between Elasticsearch and MotherDuck

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.

Elasticsearch objects MotherDuck objects
Ingest pipelines Server-side transforms applied to documents as a sync writes them. Database Shares Read-only copies of a database shared with other users or teams.
Index templates Reusable settings and mappings applied automatically to new indices a sync creates. Attached Local DuckDB Databases Local files attached alongside cloud databases for hybrid queries.
Indices Target containers for synced records; each holds a table-like collection of JSON documents. Databases Cloud-hosted DuckDB databases that scope a sync's reads and writes.
Documents The unit of sync; JSON records created, updated, and deleted by _id. Schemas Namespaces within a database used to organize synced tables.
Index mappings Field type definitions that determine how synced fields are indexed and queried. Tables The main landing target for synced records and source for analysis.
Aliases Stable read/write names that let a sync cut over between index versions without downtime. Views Modeled projections used as outbound sync sources.
What ships with Elasticsearch ⇄ MotherDuck

Connect Elasticsearch and MotherDuck for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Elasticsearch–MotherDuck connection.

Real-time

Two-way sync

Changes in Elasticsearch or MotherDuck instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Elasticsearch or MotherDuck 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 Elasticsearch or MotherDuck record.

Observability

Monitoring

Track your Elasticsearch ⇄ MotherDuck sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Elasticsearch and MotherDuck.

How the Elasticsearch and MotherDuck connectors work

Elasticsearch

Integration surface
REST API (JSON over HTTP)
Authentication
API keys or basic authentication; Elastic Cloud also issues service account tokens
Change detection
Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks
Capabilities
read · write
Rate limits
No fixed request quota; throughput is bounded by cluster sizing, thread pools, and bulk queue capacity

MotherDuck

Integration surface
SQL through DuckDB clients and drivers using a MotherDuck (md:) connection
Authentication
Access token created in MotherDuck (Settings > General > Create Token), pasted into Stacksync; database name and schema configurable if not using defaults
Change detection
Polling; no log-based CDC or webhook surface is exposed
Capabilities
read · write
Rate limits
Subject to the platform's compute and concurrency limits rather than per-request API rate limits
MotherDuck setup guide
How it works

How to connect Elasticsearch to MotherDuck — 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 Elasticsearch and MotherDuck 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
    Elasticsearch connected
    MotherDuck connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Elasticsearch and MotherDuck 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 · Elasticsearch ⇄ MotherDuck
    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
    Elasticsearch MotherDuck
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Elasticsearch and MotherDuck 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.

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 Elasticsearch and MotherDuck.

Popular · 8 of 386
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