Real-time
Two-way sync
Changes in ClickHouse or Render Postgres instantly reflect in both systems. No stale data, no manual imports.
Data warehouse ⇄ Database
ClickHouse to Render Postgres integration — real-time, two-way sync
Keep ClickHouse and Render Postgres 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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Adopted by fast-scaling companies moving mission-critical data in real time
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Why teams connect ClickHouse and Render Postgres
Connect Render Postgres 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 Render Postgres'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 Render Postgres where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Render Postgres sync into ClickHouse in real time, and result tables in ClickHouse sync back into Render Postgres, with schema and type mapping between the two systems handled for you.
Common use cases
- 01 Consolidate logs and business records from multiple sources into MergeTree tables for retention and reporting.
- 02 Land product event data alongside synced CRM accounts so analysts join usage and revenue in one place.
- 03 Two-way sync CRM or ERP objects into Render Postgres tables so product and ops teams query business data with plain SQL.
- 04 Capture row-level changes via logical replication and propagate them to a warehouse or another database in near real time.
Common sync patterns
Operational data in the warehouse, minus the pipeline
Rows from Render Postgres 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 Render Postgres, 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.
What you can sync between ClickHouse and Render Postgres
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 | Render Postgres objects | How this pairing syncs | |
|---|---|---|---|
| Views Saved queries used as curated, read-only sync sources. | Views Saved queries exposed as read-only relations; read out to BI tools or downstream syncs without duplicating transformation logic. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Materialized views Insert-time transformations that reshape incoming synced rows into aggregates. | Materialized Views Precomputed query results refreshed on demand; read for fast reporting tables that downstream systems can consume. | Same entity on both sides — records pair one-to-one and field-level changes reconcile in both directions. | |
| Tables (MergeTree family) Columnar, append-optimized tables that serve as the destination for high-volume sync loads. | Tables Relational tables with full column typing; synced two-way with CRMs, ERPs, and SaaS apps so application data is queryable as plain Postgres rows. | Tables (MergeTree family) is specific to ClickHouse and Tables to Render Postgres — each maps to any object or custom field on the other side. | |
| Databases Namespaces that group tables and scope permissions for sync users. | Schemas Namespaces that organize tables per app or environment; sync targets are scoped per schema to keep synced data isolated and tidy. | Databases is specific to ClickHouse and Schemas to Render Postgres — each maps to any object or custom field on the other side. | |
| Distributed tables Query-routing tables over cluster shards in self-managed deployments. | Columns and Types Full Postgres type system including JSONB and arrays; field mappings preserve native types instead of flattening to strings. | Distributed tables is specific to ClickHouse and Columns and Types to Render Postgres — each maps to any object or custom field on the other side. | |
| Dictionaries In-memory lookup structures refreshed from external sources, sometimes fed by syncs. | Indexes and Constraints Primary keys, unique constraints, and foreign keys; unique keys drive idempotent upserts and conflict resolution during sync. | Dictionaries is specific to ClickHouse and Indexes and Constraints to Render Postgres — each maps to any object or custom field on the other side. |
How changes propagate between ClickHouse and Render Postgres
Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.
ClickHouse Render Postgres Interval-based propagation
DetectionStacksync polls ClickHouse for changes on an incremental schedule, reading only records changed since the previous pass. No log-based CDC for consumers.
DeliveryEach detected change is applied to Render Postgres as a row-level write, with types converted between the two schemas.
Render Postgres ClickHouse Sub-second propagation
DetectionChanges in Render Postgres are captured at the source via change data capture — no polling loop against its API. Logical replication via WAL and replication slots for change data capture when enabled on the instance, with timestamp or cursor-based polling as the.
DeliveryEach detected change is applied to ClickHouse as a row-level write, with types converted between the two schemas.
Rate-limit considerations
- Render Postgres: No API rate limits — throughput is bounded by the instance's plan (CPU, RAM, connection limit); connection pooling is recommended since managed plans cap concurrent connections.
What ships with ClickHouse ⇄ Render Postgres
Connect ClickHouse and Render Postgres for flexible, real-time data sync.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every ClickHouse–Render Postgres connection.
No-code + pro-code
Workflow automation
Trigger automated workflows whenever ClickHouse or Render Postgres 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 Render Postgres record.
Observability
Monitoring
Track your ClickHouse ⇄ Render Postgres 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 Render Postgres.
How the ClickHouse and Render Postgres 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
Render Postgres
- Integration surface
- PostgreSQL wire protocol (managed Postgres on Render)
- Authentication
- Standard Postgres connection string — host, port, database, user, password with TLS; Render provides internal and external connection URLs and IP allowlisting
- Change detection
- Logical replication via WAL and replication slots for change data capture when enabled on the instance, with timestamp or cursor-based polling as the fallback
- Capabilities
- read · write · CDC
- Rate limits
- No API rate limits — throughput is bounded by the instance's plan (CPU, RAM, connection limit); connection pooling is recommended since managed plans cap concurrent connections.
How it works
How to connect ClickHouse to Render Postgres — 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 ClickHouse and Render Postgres with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
ClickHouse
connected
Render Postgres
connected
OAuth 2.0SSH tunnelSSL certificateVPC peering - 02
Choose tables
Pick the ClickHouse and Render Postgres 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 · ClickHouse ⇄ Render PostgresCustomers 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.
ClickHouse Render PostgresCompany company_name textEmail email textAmount amount numericCreated created_at timestamp
FAQ
ClickHouse and Render Postgres integration FAQ
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Yes. Stacksync provides a managed, real-time two-way integration between ClickHouse and Render Postgres: authenticate both systems, choose the objects to sync (such as ClickHouse's Views and Materialized views), 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 ClickHouse and Render Postgres 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 ClickHouse and Render Postgres connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom ClickHouse–Render Postgres integration in-house.
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Yes — Stacksync ships production-grade connectors for both ClickHouse and Render Postgres. 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 ClickHouse: No log-based CDC for consumers; incremental reads use polling on monotonic columns, and ClickHouse is usually the destination rather than the source. On Render Postgres: Logical replication via WAL and replication slots for change data capture when enabled on the instance, with timestamp or cursor-based polling as the fallback. 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 ClickHouse side: Distributed tables, Dictionaries, Tables (MergeTree family), Databases, plus custom fields where ClickHouse exposes them. On the Render Postgres side: Materialized Views, Schemas, Columns and Types, Indexes and Constraints. Stacksync auto-detects both schemas and converts types between the two systems.
SECURITY
Security teams trust 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
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