Supermetal alternative — Supermetal vs Skippr

Supermetal is a self-hosted CDC agent: one Rust binary in your VPC, on-prem, or air-gapped. It reads a source WAL, converts to Arrow, writes Parquet, and commits Iceberg (REST, Glue, or S3 Tables over S3 or GCS; Cloudflare R2 on the Iceberg announce). New tables default to Iceberg v3. JSONB, MySQL JSON, and MongoDB documents map to Iceberg variant. Merge-on-read is the default: equality deletes (Spark, Trino, DuckDB, StarRocks) or positional deletes / v3 deletion vectors (Snowflake, Databricks). Append mode writes _sm_deleted and _sm_version and you dedup at query time. Flush interval defaults to 10 seconds. Compaction is your Spark/Trino job. Iceberg docs list 0.1.13 (7 Sep 2026) as the latest changelog on that page. Sources include Postgres, MySQL, SQL Server, Oracle, MongoDB, and files. Other dests include Snowflake, Databricks, ClickHouse, Kafka, DuckDB / MotherDuck, and Postgres. Schema type promotion is not supported yet. Partition spec changes need a new table. Trial is 1,000 sync hours (EULA also caps 30 days, whichever comes first). Production Self-Hosted Unlimited starts at 10,000 USD a year, billed on compute cores, not rows. This is not Iceberg ∪ WAL. Query is after the snapshot: DuckDB, Trino, Spark, or the warehouse.

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 core-year. ELT into a warehouse is one path, not the product.

Feature	Skippr	Supermetal
Deploy	Single Rust binary, your VPC or on-prem	Single Rust binary or container, your VPC or on-prem
Schema	In-stream evolution, sibling columns	Iceberg v3 variant for JSON. Type promotion not yet
Storage	Open Iceberg on Parquet you own	Iceberg v3 (or v2) on your bucket. MoR or append
CDC	Log-based; fails closed if the dest cannot honour	WAL CDC. Postgres, MySQL, SQL Server, Oracle, Mongo
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	After commit. Compaction is a later engine job
Pricing	Free self-hosted engine	Trial 1,000 hours. Unlimited from 10,000 USD/year on cores.

What Supermetal is good at

Self-hosted CDC from operational databases into Iceberg you own, without Kafka, Spark, or Flink in the path. That is the product. v3 variant plus merge-on-read current-state tables is why some teams pick it over a Connect sink. Oracle in the source list is a real connector Skippr does not have. If the job is "this WAL into this Iceberg catalog," that is a real product.

Where the job is wider

Supermetal is a CDC agent. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight rows. Live SQL waits on the flush (10 seconds default) and then on whatever engine you point at the snapshot. Compaction is extra. Type promotion is not in yet.

Core-year math is the ops in production. Skippr will not speak Oracle CDC. Skippr also will not replace a Supermetal connector that already lands Snowflake or Databricks as the dest. OLake is a separate page.

If the job is "Supermetal CDC we already staff," Supermetal is the narrower tool. If the job is live SQL on Iceberg ∪ WAL you run, that is Skippr's job, not a later SELECT on the last snapshot.

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 Supermetal if you want a self-hosted CDC agent into Iceberg (or a warehouse dest), and Oracle or their dest list is the job.

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

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

Supermetal alternative — Supermetal vs Skippr ​

What Supermetal is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Supermetal alternative — Supermetal vs Skippr

What Supermetal is good at

Where the job is wider

Getting started

Which to choose