Canal alternative — Alibaba Canal vs Skippr

Alibaba Canal is Apache-2.0 MySQL binlog CDC. The server pretends to be a replica, dumps binlog, and hands events to clients or adapters. Current release is 1.1.8 (16 Jan 2025). Sources are MySQL 5.1 through 8.0, plus 8.4, MariaDB 11, Percona 8.0, and PolarDB-X 2.0 on that line. Native dests are Kafka, RocketMQ, Pulsar, RabbitMQ, Elasticsearch 8, and a ClickHouse adapter. Aliyun RDS binlog (including OSS offline parse and failover) is a first-class path. canal-admin is the Web UI. Cluster HA still wants ZooKeeper. There is no Postgres source. There is no Iceberg sink. The lake starts after you consume the topic. This is not a Streamhouse. There is no Iceberg ∪ WAL.

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 Canal instance. ELT into a warehouse is one path, not the product.

Feature	Skippr	Alibaba Canal
Deploy	Single Rust binary, your VPC or on-prem	Java Canal server plus client/adapter. ZK for cluster
Schema	In-stream evolution, sibling columns	TableMeta from binlog DDL. Adapter mapping is yours
Storage	Open Iceberg on Parquet you own	MQ or ES/ClickHouse. Iceberg is a sink you add
CDC	Log-based; fails closed if the dest cannot honour	MySQL binlog dump. Not Postgres
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	After the consumer. Canal is the parse, not the lake
Pricing	Free self-hosted engine	Apache-2.0. Pay JVMs, ZooKeeper, and the dest.

What Alibaba Canal is good at

A MySQL or PolarDB-X binlog that already needs to land on Kafka or RocketMQ inside an Alibaba-shaped estate. That is the product. RDS failover and OSS binlog parse are why some teams still pick it over Debezium on MySQL. If the job is "this binlog onto this bus," that is a real product.

Where the job is wider

Canal is a MySQL parser. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight rows. Iceberg is Kafka Connect or Flink after Canal.

The cluster is the ops. ZooKeeper sessions, adapter groups sharing a consumer, and a default admin password that 1.1.8 had to warn about. Skippr will not speak PolarDB-X binlog. Skippr also will not replace a Canal topic that already fans out to many consumers. Debezium is a separate page.

If the job is "Canal MySQL CDC we already staff," Canal is the narrower tool. If the job is live SQL on Iceberg you run, Canal 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 Canal if you want MySQL binlog onto Kafka or RocketMQ, and the bus after parse is enough.

Choose Skippr if you want one binary, live SQL, and Iceberg files that stay yours. Skippr will not run a Canal server.

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

Canal alternative — Alibaba Canal vs Skippr ​

What Alibaba Canal is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Canal alternative — Alibaba Canal vs Skippr

What Alibaba Canal is good at

Where the job is wider

Getting started

Which to choose