Estuary alternative — Estuary Flow vs Skippr

Estuary Flow is a SaaS CDC and batch pipe. Captures read sources into collections. Materializations write those collections to dests. One capture can fan out to many dests without a second source read. Postgres CDC uses logical replication. Iceberg materialization runs Spark on EMR Serverless (or another configured backend) and talks Glue, S3 Tables, or Snowflake Open Catalog over REST. Hard delete or soft delete is a connector setting. Delivery is exactly-once. Dekaf is a Kafka-compatible API over the same collections. Cloud list (13 Oct 2026) is 0.50 USD a GB plus 100 USD a month per connector instance for the first six, then 50 USD. Bytes count at capture and again at each delivery, including derived collections. Estuary's own example: 100 GB Postgres to Snowflake is 200 GB plus two instances, 300 USD. Developer is free to 10 GB a month and two instances. Backfills are free for 30 days. Enterprise adds private and BYOC. 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 GB-per-leg tax. ELT into a warehouse is one path, not the product.

Feature	Skippr	Estuary Flow
Deploy	Single Rust binary, your VPC or on-prem	Estuary Cloud, or Enterprise private / BYOC
Schema	In-stream evolution, sibling columns	Automatic evolution on collections
Storage	Open Iceberg on Parquet you own	Collections, then the dest. Iceberg is a Spark merge
CDC	Log-based; fails closed if the dest cannot honour	Log CDC. Exactly-once. Fan-out without a second source read
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	After materialization. Dekaf if you want Kafka consumers
Pricing	Free self-hosted engine	0.50 USD/GB per leg. Instances 100 USD then 50 USD.

What Estuary Flow is good at

A Postgres or MySQL log that needs to land in Snowflake and Iceberg without a second extract. That is the product. Two hundred connectors and a free 10 GB tier are why some teams start here before they buy MAR. If the job is "this CDC into these dests, SaaS plane," that is a real product.

Where the job is wider

Estuary is a capture/materialize pipe. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight rows. Iceberg apply is a Spark job on EMR Serverless, not a WAL you query.

GB math is the ops. Capture plus each dest is two legs. A transform is another. High-churn tables bill every change, not distinct keys. Skippr will not match Salesforce or HubSpot the way Estuary does. Skippr also will not replace an Estuary account that already fans one capture into three warehouses.

If the job is "SaaS CDC we already staff," Estuary is the narrower tool. If the job is live SQL on Iceberg you run, Estuary 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 Estuary Flow if you want SaaS CDC with fan-out dests, and the dest after materialization is enough.

Choose Skippr if you want one binary, live SQL, and Iceberg files that stay yours. Skippr will not run an Estuary capture.

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

Estuary alternative — Estuary Flow vs Skippr ​

What Estuary Flow is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Estuary alternative — Estuary Flow vs Skippr

What Estuary Flow is good at

Where the job is wider

Getting started

Which to choose