Real-time
Two-way sync
Changes in DuckDB or Elasticsearch instantly reflect in both systems. No stale data, no manual imports.
Database
DuckDB to Elasticsearch integration — real-time, two-way sync
Keep DuckDB and Elasticsearch 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
Case study
Migrated from Mulesoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect DuckDB and Elasticsearch
Keep DuckDB and Elasticsearch synchronized in real time, across engines, regions, or services, in one or both directions.
Two databases that must agree is one of the oldest problems in engineering: different engines for different workloads, separate services with overlapping reference data, a migration in flight, or regional instances that share a subset of records. Hand-rolled replication across systems means change capture, conflict handling, and type mapping, all built and maintained by your team.
Stacksync syncs tables or collections between DuckDB and Elasticsearch continuously and bi-directionally, translating types between the two engines and resolving conflicts by rules you configure. Rows written on either side appear on the other within seconds.
Common use cases
- Push aggregates computed in DuckDB out to a CRM or business tools so analysis results reach operational systems.
- Use DuckDB as a transform step: read synced Parquet exports, aggregate with SQL, and write results back to an operational database.
- Mirror support tickets into an index used for full-text search and agent-assist tooling.
- Feed enriched customer records into an index used for vector or hybrid search in AI applications.
Migration with zero-downtime cutover
When one database is replacing the other, sync both directions during the transition and switch traffic when ready, without a freeze window.
Shared reference data between services
Services that own separate databases stay consistent on the records they share, without a custom replication layer.
Regional or environment copies
Mirror selected tables to another region or environment continuously, filtered to just the rows that should travel.
What you can sync between DuckDB and Elasticsearch
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.
| DuckDB objects | Elasticsearch objects | |
|---|---|---|
| External files (Parquet/CSV/JSON) Files DuckDB queries in place without loading, common as a sync interchange format. | Data streams Append-only targets for time-series or event data pushed from source systems. | |
| Attached databases Additional database files or external systems attached into one session for cross-source queries. | Ingest pipelines Server-side transforms applied to documents as a sync writes them. | |
| Database files Single-file .duckdb databases that jobs read and write directly on disk or object storage. | Index templates Reusable settings and mappings applied automatically to new indices a sync creates. | |
| Schemas Namespaces within a database used to organize tables in sync outputs. | Indices Target containers for synced records; each holds a table-like collection of JSON documents. | |
| Tables Columnar tables created via SQL; the destination for materialized sync data. | Documents The unit of sync; JSON records created, updated, and deleted by _id. | |
| Views SQL views used to shape or filter data for downstream consumers. | Index mappings Field type definitions that determine how synced fields are indexed and queried. |
What ships with DuckDB ⇄ Elasticsearch
Connect DuckDB and Elasticsearch for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every DuckDB–Elasticsearch connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever DuckDB or Elasticsearch 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 DuckDB or Elasticsearch record.
Observability
Monitoring
Track your DuckDB ⇄ Elasticsearch sync health, view errors, and replay failed events in one click.
Trading partners
EDI
Transform legacy EDI complexity into simple database interactions between DuckDB and Elasticsearch.
How the DuckDB and Elasticsearch connectors work
DuckDB
- Integration surface
- In-process SQL engine via client libraries (Python, Node.js, JDBC, CLI); no server or network API by default
- Authentication
- None built in; access control is file-system level (MotherDuck adds token auth for its hosted service)
- Change detection
- Polling or full re-reads; no change feed or transaction log API
- Capabilities
- read · write
- Rate limits
- No API rate limits; throughput is bounded by local compute and I/O
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
How it works
How to connect DuckDB to Elasticsearch — 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 DuckDB and Elasticsearch with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
DuckDB
connected
Elasticsearch
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the DuckDB and Elasticsearch 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 · DuckDB ⇄ ElasticsearchCustomers 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.
DuckDB ElasticsearchCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
DuckDB and Elasticsearch integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between DuckDB and Elasticsearch: authenticate both systems, choose the objects to sync (such as DuckDB's External files (Parquet/CSV/JSON) and Attached databases), map fields visually, and changes propagate both ways in milliseconds — no code required.
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Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means DuckDB and Elasticsearch records are not retained after a sync operation.
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Stacksync pricing is usage-based and starts at $1,000/month, including the managed DuckDB and Elasticsearch connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom DuckDB–Elasticsearch integration in-house.
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Yes — Stacksync ships production-grade connectors for both DuckDB and Elasticsearch. 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 DuckDB: Polling or full re-reads; no change feed or transaction log API. On Elasticsearch: Polling on timestamp or sequence fields; Elasticsearch does not expose a native change feed or webhooks. 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 DuckDB side: External files (Parquet/CSV/JSON), Attached databases, Database files, Schemas, plus custom fields where DuckDB exposes them. On the Elasticsearch side: Indices, Documents, Index mappings, Aliases. Stacksync auto-detects both schemas and converts types between the two systems.
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 DuckDB and Elasticsearch.
Popular · 8 of 386
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DuckDB ⇄ AWS Aurora PostgreSQL -
DuckDB ⇄ MongoDB -
DuckDB ⇄ CockroachDB -
DuckDB ⇄ Google AlloyDB -
Elasticsearch ⇄ Oracle DB -
Elasticsearch ⇄ RavenDB -
Elasticsearch ⇄ Redis Enterprise -
Elasticsearch ⇄ SAP ASE (Sybase)
No integrations match .
