ClickPipes alternative — ClickHouse ClickPipes vs Skippr

ClickPipes is ClickHouse Cloud ingest. UI, OpenAPI, or Terraform. Destination is a ClickHouse Cloud table. Streaming GA: Kafka-API sources (Apache Kafka, Confluent Cloud, Redpanda, MSK, Azure Event Hubs, WarpStream, and kin), plus Amazon Kinesis. GCP Pub/Sub is Private Preview. Object storage GA: S3-compatible (including R2, Spaces, OVH), GCS, Azure Blob. CDC: Postgres GA, MySQL GA (billed from 1 Sep 2026), MongoDB Public Beta (free until GA), BigQuery Private Preview. CDC bytes: 0.10 USD/GB initial load or resync, 0.20 USD/GB continuous replication, plus shared compute 0.10 USD/hour on Basic (0.5 CU: 1 vCPU, 4 GiB) or 0.20 USD/hour on Scale/Enterprise (1 CU: 2 vCPU, 8 GiB). Streaming pipes: 0.20 USD per CU-hour and 0.04 USD/GB ingested (default replica is XS, 0.0125 USD/hour). Object-storage pipes bill compute only. Iceberg is not a ClickPipes destination. ClickHouse Cloud can attach an Iceberg REST or OneLake catalog and read those tables without copying them. Self-host CDC is PeerDB, not ClickPipes. This is not Iceberg ∪ WAL you query in one binary.

Skippr is an open Streamhouse you run as one Rust binary. Write skippr.yml (or the same thing in Python), discover, sync. You query live state over Iceberg ∪ WAL, and the history is ordinary Iceberg in your bucket. No ClickHouse Cloud service. ELT into a warehouse is one path, not the product.

Feature	Skippr	ClickPipes
Deploy	Single Rust binary, your VPC or on-prem	ClickHouse Cloud only
Schema	In-stream evolution, sibling columns	Destination DDL plus optional materialized views
Storage	Open Iceberg on Parquet you own	ClickHouse tables. Iceberg is a Cloud catalog read, not the pipe
CDC	Log-based; fails closed if the dest cannot honour	Postgres/MySQL GA. MongoDB beta. Dest is ClickHouse Cloud
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	ClickHouse SQL after insert. Iceberg SELECT if you attached a catalog
Pricing	Free self-hosted engine	CDC GB + CU-hour. Streaming 0.04 USD/GB plus CU-hour.

What ClickPipes is good at

Managed ingest into ClickHouse Cloud without standing a Flink job: Kafka topics, object-store files, and Postgres logical replication as a console ClickPipe. That is the product. Shared CDC compute across pipes on one service is why some ClickHouse Cloud estates skip a second CDC vendor. If the job is "this source into this ClickHouse Cloud table," that is a real product.

Where the job is wider

ClickPipes is Cloud ingest. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight lake rows. The pipe will not write Iceberg. Catalog Iceberg is a read of files that already exist. ClickPipes will not run on a self-hosted ClickHouse cluster. That path is PeerDB or a Kafka sink you staff.

GB and CU-hour math is the ops, plus the ClickHouse Cloud service the rows land in. Skippr will not replace a ClickPipe that already lands ClickHouse Cloud. Skippr also will not write MergeTree. PeerDB is the self-host CDC page. ClickHouse as a database is a later page.

If the job is "ClickHouse Cloud we already pay," ClickPipes is the narrower tool. If the job is live SQL on Iceberg you run, the pipe was never that.

Getting started

Install skipprd from the install guide, or pip install skippr. The three tabs write the same skippr.yml. Then discover, sync, and query.

YAMLCLIPython

yaml

skippr:
  workspace: analytics
  skipprd_el_storage_mode: local

pipelines:
  orders:
    data_source: data_sources.app_db
    data_sink: data_sinks.lake

data_sources:
  app_db:
    Postgres:
      host: db.internal
      user: skippr_reader
      password: ${APP_DB_PASSWORD}
      database: app
      tables: [orders, customers]
      cdc_mode: snapshot_then_cdc

data_sinks:
  lake:
    AthenaIceberg:
      warehouse: s3://my-iceberg-warehouse/
      glue_database_name: analytics
      athena_workgroup_name: primary
      athena_results_s3_bucket: my-athena-results
      region: us-east-1
    schema_sink: schema_sinks.lake_schema

schema_sinks:
  lake_schema:
    AthenaIceberg:
      warehouse: s3://my-iceberg-warehouse/
      glue_database_name: analytics
      athena_workgroup_name: primary
      athena_results_s3_bucket: my-athena-results
      region: us-east-1

bash

skipprd --workspace analytics --storage-mode local connect data-source postgres \
  --pipeline orders \
  --name app_db \
  --host db.internal \
  --user skippr_reader \
  --password '${APP_DB_PASSWORD}' \
  --database app \
  --tables orders \
  --tables customers \
  --cdc-mode snapshot_then_cdc

skipprd connect data-sink athenaiceberg \
  --pipeline orders \
  --name lake \
  --warehouse s3://my-iceberg-warehouse/ \
  --glue-database-name analytics \
  --athena-workgroup-name primary \
  --athena-results-s3-bucket my-athena-results \
  --region us-east-1

skipprd connect schema-sink athenaiceberg \
  --pipeline orders \
  --name lake_schema

python

from skippr import (
    Config,
    DataSinkAthenaIceberg,
    DataSourcePostgres,
    DataSourcePostgresSourceCdcMode,
    EnvRef,
    LocalStorage,
    Pipeline,
)

cfg = Config().workspace("analytics").storage(LocalStorage())

app_db = cfg.data_source(
    "app_db",
    DataSourcePostgres(
        host="db.internal",
        user="skippr_reader",
        password=EnvRef("APP_DB_PASSWORD"),
        database="app",
        tables=["orders", "customers"],
        cdc_mode=DataSourcePostgresSourceCdcMode.SNAPSHOTTHENCDC,
    ),
)

lake = cfg.data_sink(
    "lake",
    DataSinkAthenaIceberg(
        warehouse="s3://my-iceberg-warehouse/",
        glue_database_name="analytics",
        athena_workgroup_name="primary",
        athena_results_s3_bucket="my-athena-results",
        region="us-east-1",
    ),
    schema_sink="lake_schema",
)

cfg.pipeline("orders", Pipeline(data_source=app_db, data_sink=lake))
cfg.save("skippr.yml")

bash

export APP_DB_PASSWORD='your-postgres-password'
skipprd discover --pipeline orders
skipprd sync --pipeline orders --once
skipprd query "SELECT count(*) FROM analytics.orders"

Which to choose

Choose ClickPipes if you already run ClickHouse Cloud, and a managed pipe into that service is the job.

Choose Skippr if you want one binary, live SQL on Iceberg ∪ WAL, and files that stay yours. Skippr will not run ClickPipes.

Install from Install. Connector and query reference live in Developer Docs. For optional onboarding in your VPC, Enterprise Jumpstart or Contact.

ClickPipes alternative — ClickHouse ClickPipes vs Skippr ​

What ClickPipes is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

ClickPipes alternative — ClickHouse ClickPipes vs Skippr

What ClickPipes is good at

Where the job is wider

Getting started

Which to choose