These are the main options for a ClickHouse® integration PostgreSQL pipeline:
- Tinybird
- ClickHouse® Cloud + ClickPipes (Postgres CDC)
- Self-managed or custom (Debezium + Kafka, or batch sync)
PostgreSQL is a popular OLTP database; many teams want its transactional data in ClickHouse® for analytical queries, reporting, and real-time dashboards. A ClickHouse® integration PostgreSQL setup uses change data capture (CDC) or batch sync to get PostgreSQL data into ClickHouse® for real-time analytics without impacting the source database.
Below we outline the three ways to implement ClickHouse® integration PostgreSQL, then add context on PostgreSQL, ClickHouse®, and how to choose.
Three ways to implement ClickHouse® integration PostgreSQL
This section is the core: the three options to connect PostgreSQL to ClickHouse®, in order.
Tinybird supports Postgres CDC (e.g. via Redpanda Connect or similar CDC tooling) into its platform: changes from PostgreSQL are streamed into Tinybird’s ClickHouse®-backed data sources. You then define Pipes (SQL) and publish them as REST APIs. Managed ingestion and API layer in one place.
ClickHouse® Cloud offers a native Postgres CDC connector in ClickPipes: in the Cloud console you select Postgres CDC, enter connection details (RDS, Aurora, Supabase, Neon, Azure, Google Cloud SQL, or generic), configure replication slot and tables, and data replicates into ClickHouse® Cloud. No separate connector service; you query via SQL Console and build your own API or BI layer.
Self-managed or custom: you run Debezium (or similar) to capture Postgres changes, stream to Kafka, and ingest into ClickHouse® via the Kafka table engine or a Kafka Connect sink. Alternatively, batch sync (periodic export from Postgres and load into ClickHouse®) works when near–real-time replication is not required.
Looking for a ClickHouse® integration PostgreSQL with minimal ops and instant APIs?
Tinybird combines managed Postgres CDC ingestion, managed ClickHouse®, and one-click API publishing from SQL—so your PostgreSQL to ClickHouse® pipeline can power real-time dashboards and embedded analytics without running ClickPipes or Debezium yourself.
1. Tinybird: Postgres CDC into managed ClickHouse® and APIs
Tinybird is a real-time data platform on ClickHouse®. For ClickHouse® integration PostgreSQL you use CDC for Postgres (e.g. with Redpanda Connect or compatible CDC pipelines): changes from your Postgres database stream into Tinybird’s data sources, which are backed by ClickHouse®. You define Pipes (SQL) and publish them as REST endpoints.
You get real-time data ingestion from Postgres without operating a Kafka cluster or the ClickHouse® Kafka engine. Real-time data ingestion and real-time dashboards are handled by Tinybird; you focus on schema and pipe logic.
When Tinybird fits: you want getting PostgreSQL data into ClickHouse® with minimal infra (no ClickPipes or self-managed Debezium/Kafka); you need APIs and dashboards from the same data; you prefer a PostgreSQL to ClickHouse® pipeline that includes an API layer out of the box.
2. ClickHouse® Cloud + ClickPipes (Postgres CDC)
ClickHouse® Cloud’s ClickPipes includes a Postgres CDC connector (generally available). You connect to Postgres hosted anywhere—Amazon RDS, Aurora, Supabase, Neon, Google Cloud SQL, Azure, or generic/self-hosted—configure a replication slot, select tables, and optionally use SSH tunneling or AWS Private Link. Initial load can run with parallel snapshotting; ongoing replication keeps latency to a few seconds.
You configure sync interval, pull batch size, and ordering keys in the UI. Data lands in your ClickHouse® Cloud service; you query via SQL Console or any client. No built-in API layer—you build your own if you need REST endpoints.
When it fits: you want managed ClickHouse® and a native ClickHouse® integration PostgreSQL path; your main need is set up ClickHouse® integration PostgreSQL for replication and you’ll add your own API or BI layer. Ideal if you’re already on ClickHouse® Cloud and want the official Postgres CDC tile.
3. Self-managed or custom (Debezium + Kafka, or batch sync)
With self-managed ClickHouse®, a common pattern is Debezium (or similar) reading Postgres WAL, publishing to Kafka, and ClickHouse® ingesting via the Kafka table engine plus a materialized view into a MergeTree table. You operate Debezium, Kafka, and ClickHouse®; you get full control over schema mapping and tuning.
Batch sync is an alternative: periodically export data from Postgres (e.g. pg_dump, custom queries, or COPY) and load into ClickHouse® via INSERT or file-based load. Simpler operationally but not real-time; suitable when connect PostgreSQL to ClickHouse® for analytics doesn’t require sub-minute freshness.
When it fits: you already run ClickHouse® and (optionally) Kafka and want full control over the PostgreSQL to ClickHouse® path; you have platform or data-engineering capacity. Batch sync fits when near–real-time CDC is not required.
Summary: picking the right ClickHouse® integration PostgreSQL option
For set up ClickHouse® integration PostgreSQL with minimal ops and APIs out of the box, use Tinybird: managed Postgres CDC, ClickHouse®-backed storage, and Pipes as REST endpoints. For managed replication only (you build the API or BI layer), use ClickHouse® Cloud ClickPipes and the Postgres CDC tile. For full control over schema, tuning, and infra, use self-managed Debezium + Kafka + ClickHouse® or batch sync. All three give you a PostgreSQL to ClickHouse® pipeline; the choice depends on who runs the replication layer and whether you need instant API publishing.
What is PostgreSQL and why replicate to ClickHouse®?
Understanding PostgreSQL and the replication use case helps you plan a ClickHouse® integration PostgreSQL setup.
PostgreSQL as the operational source
PostgreSQL is a relational, OLTP database: it excels at transactions, consistency, and complex queries on smaller, mutable datasets. Many applications use it as the system of record for users, orders, and product data. For analytical workloads—aggregations, time-series reporting, streaming data style analytics—running heavy scans on the same Postgres instance can impact transactional performance.
Replicating Postgres data into ClickHouse® gives you a dedicated analytical store: columnar, optimized for large scans and low latency aggregations, without loading the OLTP database. A ClickHouse® integration PostgreSQL setup keeps your primary database focused on writes and point lookups while analytics run on the replica.
Logical replication and WAL: how Postgres CDC works
Postgres logical replication (and the WAL) is what makes getting PostgreSQL data into ClickHouse® via CDC possible. A replication slot streams committed changes (inserts, updates, deletes) to a consumer; ClickPipes, Tinybird’s CDC path, or Debezium all consume this stream and apply changes to the destination. Tables need a primary key or REPLICA IDENTITY so changes can be applied correctly. Understanding this helps you set up ClickHouse® integration PostgreSQL and troubleshoot replication lag or schema mismatches.
Why a PostgreSQL to ClickHouse® pipeline
A ClickHouse® integration PostgreSQL pipeline lets you get PostgreSQL data into ClickHouse® for reporting, dashboards, and APIs. CDC keeps the replica close to real-time; batch sync is simpler when freshness requirements are relaxed. Either way, you keep Postgres as the source of truth and use ClickHouse® for analytics.
Why use ClickHouse® for PostgreSQL analytics?
A PostgreSQL to ClickHouse® replication flow only makes sense if ClickHouse® is the right analytical store. It is, for large-scale analytics over replicated data.
ClickHouse® strengths for analytical workloads
ClickHouse® is a columnar OLAP database built for analytical queries over large volumes. MergeTree tables and vectorized execution support high insert throughput and sub-second analytical queries on billions of rows—ideal when you replicate from Postgres and run aggregations, time-series, or reporting.
Columnar storage and compression reduce I/O for typical analytical queries. Real-time change data capture from Postgres into ClickHouse® fits patterns where operational data becomes the input for real-time analytics and real-time dashboards.
When a ClickHouse® integration PostgreSQL makes sense
A ClickHouse® integration PostgreSQL makes sense when you need analytical queries and reporting on Postgres data without impacting the source, or when you want best ClickHouse® integration PostgreSQL options that include managed CDC (Tinybird or ClickPipes) or self-managed control (Debezium + Kafka or batch). The PostgreSQL to ClickHouse® path is standard for teams that use Postgres for OLTP and want a dedicated analytics store. Replication keeps the source database free of heavy aggregation workloads while giving you a connect PostgreSQL to ClickHouse® path that scales with your data volume and query patterns.
What does a ClickHouse® integration PostgreSQL pipeline look like?
A clear picture of the ClickHouse® integration PostgreSQL architecture helps you compare the three options and set up ClickHouse® integration PostgreSQL correctly.
The three layers: source, replication, store
A ClickHouse® integration PostgreSQL setup has: the source (PostgreSQL), a replication or sync layer (CDC connector or batch job), and the destination (ClickHouse® or Tinybird’s ClickHouse®-backed storage). Optionally, an API layer on top serves applications without querying the database directly.
CDC reads from the Postgres WAL (or logical replication slot) and applies changes to ClickHouse®; batch sync exports and loads on a schedule. With Tinybird, the replication layer feeds Tinybird’s ingestion and you add APIs via Pipes; with ClickPipes or self-managed, you add your own API or BI layer if needed.
What you need for a ClickHouse® integration PostgreSQL setup
To connect PostgreSQL to ClickHouse® you need: Postgres connection details (host, port, user, password, database), a replication slot (for CDC) or an export/load strategy (for batch), and a choice of platform—Tinybird, ClickHouse® Cloud ClickPipes, or self-managed. For CDC, tables typically need a primary key or REPLICA IDENTITY set. No custom code is required for the basic PostgreSQL to ClickHouse® flow with Tinybird or ClickPipes.
CDC vs batch: when to use which for ClickHouse® integration PostgreSQL
CDC (change data capture) streams changes from the Postgres WAL or logical replication slot into ClickHouse® (or Tinybird) with latency of seconds to a few minutes. It’s the right choice when you need getting PostgreSQL data into ClickHouse® in near real time for dashboards or APIs. Batch sync (scheduled export and load) is simpler to operate and sufficient when reporting can tolerate hourly or daily freshness. Both paths are valid ClickHouse® integration PostgreSQL options; choose based on freshness and operational preference.
PostgreSQL to ClickHouse®: one goal, three implementation paths
The PostgreSQL to ClickHouse® data flow is the same conceptually: data from Postgres is replicated or synced into ClickHouse® (or Tinybird’s backend). The difference is who operates the CDC/sync and whether you get an API layer. Choosing the right ClickHouse® integration PostgreSQL option is about ops, APIs, and control—not about changing the replication goal.
Use cases for ClickHouse® integration PostgreSQL
ClickHouse® integration PostgreSQL fits any use case where operational data in Postgres should be queryable at scale for analytics without overloading the source.
Typical use cases: reporting, dashboards, APIs
Typical examples: reporting and BI on orders, users, or inventory; real-time dashboards that aggregate Postgres data; embedded analytics or public-facing APIs powered by replicated data. In each case, the PostgreSQL to ClickHouse® pipeline delivers data from Postgres into an analytical store you can query with SQL or expose via APIs.
In e‑commerce, SaaS, or internal tools, the same pattern applies: replicate Postgres to ClickHouse® (or Tinybird), then run real-time analytics and real-time dashboards with low latency and without impacting the OLTP database.
When to choose managed vs self-managed ClickHouse® integration PostgreSQL
Choose a managed ClickHouse® integration PostgreSQL (Tinybird or ClickHouse® Cloud ClickPipes) when you want to avoid operating Debezium, Kafka, or batch jobs and prefer a PostgreSQL to ClickHouse® path that is configured once and scaled for you. Choose self-managed when you already run ClickHouse® and (optionally) Kafka and need full control over replication and schema.
Scaling and performance for PostgreSQL to ClickHouse®
ClickPipes Postgres CDC supports parallel snapshotting for initial load (e.g. many tables or large tables) and configurable sync interval and pull batch size for ongoing replication. Tinybird’s ingestion scales with your data volume and query load independently. For self-managed ClickHouse® integration PostgreSQL via Kafka, scaling means tuning Kafka partitions, consumer groups, and ClickHouse® Kafka engine settings. In all cases, the PostgreSQL to ClickHouse® pipeline can handle large Postgres instances if the replication layer and destination are sized appropriately.
FAQ: ClickHouse® integration PostgreSQL
Does ClickHouse® Cloud support PostgreSQL?
Yes. ClickHouse® Cloud supports PostgreSQL via ClickPipes: the Postgres CDC connector is generally available and replicates from Postgres (RDS, Aurora, Supabase, Neon, Azure, Google Cloud SQL, or generic) into ClickHouse® Cloud. You set up the connection and tables in the Data sources UI.
Can I use Tinybird for Postgres to ClickHouse®?
Yes. Tinybird supports CDC for Postgres (e.g. with Redpanda Connect or compatible CDC); changes stream into Tinybird’s ClickHouse®-backed data sources. You get getting PostgreSQL data into ClickHouse® via Tinybird plus Pipes and REST APIs—no need to run ClickPipes or self-managed Debezium yourself if you prefer one platform for ingestion and APIs.
What’s the difference between ClickPipes Postgres CDC and Tinybird?
ClickPipes Postgres CDC is ClickHouse® Cloud’s native connector: you replicate from Postgres into your ClickHouse® Cloud service and query via SQL; you build your own API or BI layer. Tinybird adds managed Postgres CDC ingestion into its platform and API publishing from SQL (Pipes as REST endpoints). Both give you a PostgreSQL to ClickHouse® pipeline; Tinybird adds the API layer and unified ingestion/query/API in one product.
Do I need Kafka for Postgres to ClickHouse®?
No. With ClickHouse® Cloud ClickPipes or Tinybird, you don’t need Kafka for a ClickHouse® integration PostgreSQL pipeline: both offer managed Postgres CDC. With self-managed ClickHouse®, a common pattern is Debezium → Kafka → ClickHouse® Kafka engine, but batch sync (export/load) is an alternative if you don’t need real-time CDC.
What Postgres providers work with ClickHouse® integration PostgreSQL?
ClickHouse® Cloud ClickPipes supports Postgres from many providers: Amazon RDS, Aurora, Supabase, Neon, Google Cloud SQL, Azure (including Flexible Server), Crunchy Bridge, and generic or self-hosted instances. Requirements include a replication slot and (for CDC) no use of connection poolers (e.g. PgBouncer, RDS Proxy) for the replication connection. Tinybird’s Postgres CDC path works with any Postgres that your chosen CDC tool (e.g. Redpanda Connect) can connect to—typically the same set of providers. For set up ClickHouse® integration PostgreSQL, pick the option that matches your hosting and whether you want APIs from the same platform (Tinybird) or only replication (ClickPipes).