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

Keep Elasticsearch and TimescaleDB 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

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Why teams connect Elasticsearch and TimescaleDB

Keep Elasticsearch and TimescaleDB 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 Elasticsearch and TimescaleDB 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 product catalog data from an ERP or commerce database into Elasticsearch for storefront search.
  • Mirror support tickets into an index used for full-text search and agent-assist tooling.
  • Keep device or asset reference tables bi-directionally in sync between TimescaleDB and an ERP.
  • Consolidate metrics from several services into one hypertable to serve a single reporting layer.

Cross-engine sync

Keep the same dataset live in both Elasticsearch and TimescaleDB, so each workload runs on the engine that suits it.

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.

What you can sync between Elasticsearch and TimescaleDB

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 TimescaleDB objects
Data streams Append-only targets for time-series or event data pushed from source systems. Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems.
Ingest pipelines Server-side transforms applied to documents as a sync writes them. Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data.
Index templates Reusable settings and mappings applied automatically to new indices a sync creates. Views Standard SQL views used to shape or filter data for consumers.
Indices Target containers for synced records; each holds a table-like collection of JSON documents. Schemas Postgres namespaces used to separate synced datasets by team or environment.
Documents The unit of sync; JSON records created, updated, and deleted by _id. Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs.
Index mappings Field type definitions that determine how synced fields are indexed and queried. Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly.
What ships with Elasticsearch ⇄ TimescaleDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Elasticsearch or TimescaleDB 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 TimescaleDB record.

Observability

Monitoring

Track your Elasticsearch ⇄ TimescaleDB 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 TimescaleDB.

How the Elasticsearch and TimescaleDB 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

TimescaleDB

Integration surface
SQL wire protocol (PostgreSQL)
Authentication
Database credentials
Change detection
Log-based capture via PostgreSQL logical decoding where the deployment allows it — hypertable changes surface on the underlying chunk tables and must be remapped to the parent — or timestamp-based polling on time columns; regular Postgres tables replicate through standard logical replication
Capabilities
read · write · CDC
Rate limits
No API rate limits; throughput is bounded by database resources and connection limits.
How it works

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

    Choose tables

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

Elasticsearch and TimescaleDB 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 Elasticsearch and TimescaleDB.

Popular · 8 of 386
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