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Data warehouse ⇄ Database

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

Keep ClickHouse 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.

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Why teams connect ClickHouse and TimescaleDB

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

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

Common use cases

  • Consolidate logs and business records from multiple sources into MergeTree tables for retention and reporting.
  • Land product event data alongside synced CRM accounts so analysts join usage and revenue in one place.
  • 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.

Offload heavy reads

Point analytical queries at the synced copy in ClickHouse and keep TimescaleDB focused on its operational workload.

Operational data in the warehouse, minus the pipeline

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

Serve warehouse results at database speed

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

What you can sync between ClickHouse 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.

ClickHouse objects TimescaleDB objects
Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. Continuous Aggregates Incrementally maintained rollups that serve as pre-aggregated read sources for downstream systems.
Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. Regular PostgreSQL Tables Relational reference data such as devices, tenants, or accounts synced alongside the series data.
Databases Namespaces that group tables and scope permissions for sync users. Views Standard SQL views used to shape or filter data for consumers.
Views Saved queries used as curated, read-only sync sources. Schemas Postgres namespaces used to separate synced datasets by team or environment.
Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. Hypertables Time-partitioned tables that hold the main time-series data; the primary read and write target in syncs.
Distributed tables Query-routing tables over cluster shards in self-managed deployments. Chunks Time-bounded partitions of a hypertable; syncs read and write through the parent hypertable and never address chunks directly.
What ships with ClickHouse ⇄ TimescaleDB

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

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

Real-time

Two-way sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever ClickHouse 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 ClickHouse or TimescaleDB record.

Observability

Monitoring

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

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between ClickHouse and TimescaleDB.

How the ClickHouse and TimescaleDB connectors work

ClickHouse

Integration surface
Native TCP protocol and HTTP interface; standard SQL dialect, with MySQL and PostgreSQL wire compatibility available
Authentication
Database credentials (username/password); ClickHouse Cloud issues per-service credentials over TLS
Change detection
No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source
Capabilities
read · write

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 ClickHouse 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 ClickHouse 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
    ClickHouse connected
    TimescaleDB connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

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

ClickHouse 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.

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 ClickHouse and TimescaleDB.

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