These are the main options for a ClickHouse® integration MySQL pipeline:
- Tinybird
- ClickHouse® Cloud + ClickPipes (MySQL CDC)
- Self-managed or custom (Debezium + Kafka, or batch sync)
MySQL is a widely used OLTP database; many teams want its transactional data in ClickHouse® for analytical queries, reporting, and real-time dashboards. A ClickHouse® integration MySQL setup uses change data capture (CDC) or batch sync to get MySQL data into ClickHouse® for real-time analytics without impacting the source database.
Below we outline the three ways to implement ClickHouse® integration MySQL, then add context on MySQL, ClickHouse®, and how to choose.
Three ways to implement ClickHouse® integration MySQL
This section is the core: the three options to connect MySQL to ClickHouse®, in order.
Tinybird supports CDC for MySQL (e.g. via Redpanda Connect or compatible CDC tooling) into its platform: changes from MySQL 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 MySQL CDC connector in ClickPipes (public beta): you connect to MySQL (RDS, Aurora, Google Cloud SQL, Azure, or self-hosted), configure replication (GTID or binlog position), select 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 MySQL binlog changes, stream to Kafka, and ingest into ClickHouse® via the Kafka table engine or a Kafka Connect sink. Alternatively, batch sync (periodic export from MySQL and load into ClickHouse®) works when near–real-time replication is not required.
Looking for a ClickHouse® integration MySQL with minimal ops and instant APIs?
Tinybird combines managed MySQL CDC ingestion, managed ClickHouse®, and one-click API publishing from SQL—so your MySQL to ClickHouse® pipeline can power real-time dashboards and embedded analytics without running ClickPipes or Debezium yourself.
1. Tinybird: MySQL CDC into managed ClickHouse® and APIs
Tinybird is a real-time data platform on ClickHouse®. For ClickHouse® integration MySQL you use CDC for MySQL (e.g. with Redpanda Connect or compatible CDC pipelines): changes from your MySQL 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 MySQL 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 MySQL 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 MySQL to ClickHouse® pipeline that includes an API layer out of the box.
Prerequisites: MySQL with binlog enabled and binlog_format=ROW, and (if you use CDC) a Kafka cluster plus a MySQL CDC connector such as Redpanda Connect. Data flows MySQL binlog → connector → Kafka → Tinybird Kafka connector → Tinybird data sources. End-to-end latency is typically seconds to a few minutes. You run MySQL and optionally the CDC connector and Kafka; Tinybird runs ingestion, storage, and API publishing.
2. ClickHouse® Cloud + ClickPipes (MySQL CDC)
ClickHouse® Cloud's ClickPipes includes a MySQL CDC connector (public beta). You connect to MySQL hosted anywhere—Amazon RDS, Aurora, Google Cloud SQL, Azure, or self-hosted—configure binlog replication (GTID or position), select tables, and optionally use SSH tunneling or 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 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 MySQL path; your main need is set up ClickHouse® integration MySQL for replication and you'll add your own API or BI layer. Ideal if you're already on ClickHouse® Cloud and want the official MySQL CDC tile.
Prerequisites: MySQL with log_bin=ON, binlog_format=ROW, and binlog_row_image=FULL; a user with REPLICATION CLIENT and REPLICATION SLAVE; network access (or SSH tunnel) from ClickPipes to MySQL. Data flows MySQL → ClickPipes MySQL CDC connector → ClickHouse® Cloud. Replication latency is on the order of a few seconds. ClickHouse® Cloud operates the connector and ingestion; you operate MySQL and add your own API or BI layer.
3. Self-managed or custom (Debezium + Kafka, or batch sync)
With self-managed ClickHouse®, a common pattern is Debezium (or similar) reading the MySQL binlog, 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 MySQL (e.g. mysqldump, custom queries, or SELECT INTO OUTFILE) and load into ClickHouse® via INSERT or file-based load. Simpler operationally but not real-time; suitable when connect MySQL 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 MySQL to ClickHouse® path; you have platform or data-engineering capacity. Batch sync fits when near–real-time CDC is not required.
For CDC: prerequisites are MySQL binlog (ROW format), a Kafka cluster, and Debezium (or similar). Data flows MySQL → Debezium → Kafka → ClickHouse® Kafka table engine (and typically a materialized view into MergeTree). Latency is seconds to a few minutes. For batch: you export (e.g. mysqldump, SELECT INTO OUTFILE) and load on a schedule; you operate all components.
Summary: picking the right ClickHouse® integration MySQL option
For set up ClickHouse® integration MySQL with minimal ops and APIs out of the box, use Tinybird: managed MySQL 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 MySQL CDC connector. For full control over schema, tuning, and infra, use self-managed Debezium + Kafka + ClickHouse® or batch sync. All three give you a MySQL to ClickHouse® pipeline; the choice depends on who runs the replication layer and whether you need instant API publishing. When deciding: weigh freshness (sub-minute CDC vs batch hourly/daily), data volume and table count (parallel snapshot and scaling), team ability to run Kafka and Debezium vs managed connectors, existing Kafka (reuse for CDC) vs no Kafka (managed or batch), and cost predictability (Tinybird, ClickPipes) vs flexibility (self-managed).
What is MySQL and why replicate to ClickHouse®?
Understanding MySQL and the replication use case helps you plan a ClickHouse® integration MySQL setup.
MySQL as the operational source
MySQL is a relational, OLTP database: it excels at transactions, consistency, and high concurrency for application workloads. 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 MySQL instance can impact transactional performance.
Replicating MySQL 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 MySQL setup keeps your primary database focused on writes and point lookups while analytics run on the replica.
Binlog and CDC: how MySQL replication works
MySQL's binary log (binlog) is what makes getting MySQL data into ClickHouse® via CDC possible. The binlog records row-level changes; Debezium, ClickPipes, or Tinybird's CDC path consume this stream and apply changes to the destination. You must set binlog_format=ROW (and for some connectors binlog_row_image=FULL); GTID or binlog position can be used for replication. Tables typically need a primary key for correct apply of updates and deletes. Sufficient binlog retention is critical: if the connector falls behind or is paused and the offset is invalidated (e.g. after failover), a full resync may be required. Understanding this helps you set up ClickHouse® integration MySQL and troubleshoot replication lag or schema mismatches.
Why a MySQL to ClickHouse® pipeline
A ClickHouse® integration MySQL pipeline lets you get MySQL 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 MySQL as the source of truth and use ClickHouse® for analytics.
Why use ClickHouse® for MySQL analytics?
A MySQL 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 MySQL and run aggregations, time-series, or reporting.
Columnar storage and compression reduce I/O for typical analytical queries. Real-time change data capture from MySQL into ClickHouse® fits patterns where operational data becomes the input for real-time analytics and real-time dashboards.
When a ClickHouse® integration MySQL makes sense
A ClickHouse® integration MySQL makes sense when you need analytical queries and reporting on MySQL data without impacting the source, or when you want best ClickHouse® integration MySQL options that include managed CDC (Tinybird or ClickPipes) or self-managed control (Debezium + Kafka or batch). The MySQL to ClickHouse® path is standard for teams that use MySQL for OLTP and want a dedicated analytics store. Replication keeps the source database free of heavy aggregation workloads while giving you a connect MySQL to ClickHouse® path that scales with your data volume and query patterns.
What does a ClickHouse® integration MySQL pipeline look like?
A clear picture of the ClickHouse® integration MySQL architecture helps you compare the three options and set up ClickHouse® integration MySQL correctly.
The three layers: source, replication, store
A ClickHouse® integration MySQL setup has: the source (MySQL), 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 MySQL binlog 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. For validation and observability: compare source binlog position to consumer offset (e.g. Kafka consumer lag) and alert when lag exceeds your SLA; periodically reconcile row counts or distinct keys between MySQL and ClickHouse® for critical tables; monitor connector and consumer health, error rates, and any dead-letter or quarantine tables; use event-time in queries and ReplacingMergeTree or argMax for late or out-of-order data, and define a freshness SLA (e.g. p99 event time lag).
What you need for a ClickHouse® integration MySQL setup
To connect MySQL to ClickHouse® you need: MySQL connection details (host, port, user, password, database), binlog enabled (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. No custom code is required for the basic MySQL to ClickHouse® flow with Tinybird or ClickPipes.
Failure modes to plan for: schema drift (new or dropped columns in MySQL) requires destination schema updates or nullable columns. ClickHouse® is append-optimized—represent deletes and updates via ReplacingMergeTree with a version column or soft-delete flags, and use FINAL or query-time argMax for consistent reads. CDC is at-least-once; duplicate events are common (connector restart, Kafka rebalance)—deduplicate by primary key and version. Initial snapshot and CDC can both emit the same rows; deduplicate by key and version/timestamp. If consumer lag exceeds binlog retention, backfill or full resync is required; backfill from export or object storage without blocking live CDC where possible.
CDC vs batch: when to use which for ClickHouse® integration MySQL
CDC (change data capture) streams changes from the MySQL binlog into ClickHouse® (or Tinybird) with latency of seconds to a few minutes. It's the right choice when you need getting MySQL 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 MySQL options; choose based on freshness and operational preference.
MySQL to ClickHouse®: one goal, three implementation paths
The MySQL to ClickHouse® data flow is the same conceptually: data from MySQL 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 MySQL option is about ops, APIs, and control—not about changing the replication goal.
Use cases for ClickHouse® integration MySQL
ClickHouse® integration MySQL fits any use case where operational data in MySQL 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 MySQL data; embedded analytics or public-facing APIs powered by replicated data. In each case, the MySQL to ClickHouse® pipeline delivers data from MySQL 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 MySQL 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 MySQL
Choose a managed ClickHouse® integration MySQL (Tinybird or ClickHouse® Cloud ClickPipes) when you want to avoid operating Debezium, Kafka, or batch jobs and prefer a MySQL 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 MySQL to ClickHouse®
ClickPipes MySQL 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 MySQL via Kafka, scaling means tuning Kafka partitions, consumer groups, and ClickHouse® Kafka engine settings. In all cases, the MySQL to ClickHouse® pipeline can handle large MySQL instances if the replication layer and destination are sized appropriately.
Frequently Asked Questions (FAQs)
Does ClickHouse® Cloud support MySQL?
Yes. ClickHouse® Cloud supports MySQL via ClickPipes: the MySQL CDC connector is in public beta and replicates from MySQL (RDS, Aurora, Google Cloud SQL, Azure, or self-hosted) into ClickHouse® Cloud. You set up the connection and tables in the Data sources UI.
Can I use Tinybird for MySQL to ClickHouse®?
Yes. Tinybird supports CDC for MySQL (e.g. with Redpanda Connect or compatible CDC); changes stream into Tinybird's ClickHouse®-backed data sources. You get getting MySQL 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 MySQL CDC and Tinybird?
ClickPipes MySQL CDC is ClickHouse® Cloud's native connector: you replicate from MySQL into your ClickHouse® Cloud service and query via SQL; you build your own API or BI layer. Tinybird adds managed MySQL CDC ingestion into its platform and API publishing from SQL (Pipes as REST endpoints). Both give you a MySQL to ClickHouse® pipeline; Tinybird adds the API layer and unified ingestion/query/API in one product.
Do I need Kafka for MySQL to ClickHouse®?
No. With ClickHouse® Cloud ClickPipes or Tinybird, you don't need Kafka for a ClickHouse® integration MySQL pipeline: both offer managed MySQL 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 MySQL providers work with ClickHouse® integration MySQL?
ClickHouse® Cloud ClickPipes supports MySQL from many providers: Amazon RDS, Aurora, Google Cloud SQL, Azure (including Flexible Server), and self-hosted MySQL or MariaDB. Requirements include binlog enabled and (for CDC) appropriate user privileges. Tinybird's MySQL CDC path works with any MySQL that your chosen CDC tool (e.g. Redpanda Connect) can connect to—typically the same set of providers. For set up ClickHouse® integration MySQL, pick the option that matches your hosting and whether you want APIs from the same platform (Tinybird) or only replication (ClickPipes).
Is a ClickHouse® integration MySQL good for real-time dashboards?
Yes. With CDC, your MySQL to ClickHouse® replica is updated in seconds. You can power real-time dashboards and real-time analytics from that data without querying MySQL directly. Tinybird adds instant REST APIs from SQL so you can serve dashboards and embedded analytics from the same pipeline.