Pathway alternative — Pathway vs Skippr

Pathway is a Python Table API on a Rust streaming engine. Latest GitHub release is 0.32.1 (1 Aug 2026). Licence is BSL 1.1, converting to Apache-2.0 four years after merge. Community is free to self-host in production at 4 CPU cores and 8 GiB RAM per node (not for reselling stream processing). Scale uses pathway.set_license_key(): 4 cores, 16 GiB, and the enterprise connectors. Iceberg (pw.io.iceberg.read / pw.io.iceberg.write) is Scale or Enterprise only, same as Delta Lake and SharePoint. Community I/O includes Kafka, Redpanda, Postgres, Pub/Sub, S3, files, HTTP, and custom Python. 0.32.1 added ClickHouse write (stream_of_changes or snapshot into ReplacingMergeTree), DuckDB, and vector-store sinks. Iceberg writes still omit date and map<K,V>; structs map to positional tuples. CDC is a connector you pick (Kafka, Postgres, Airbyte), not a WAL-to-Iceberg engine. Enterprise is a custom quote (docs list up to 24 TiB RAM and 128 cores × 40 nodes, Helm, managed). 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 Pathway license key. ELT into a warehouse is one path, not the product.

Feature	Skippr	Pathway
Deploy	Single Rust binary, your VPC or on-prem	`pip` / Docker / Jupyter, or Pathway managed
Schema	In-stream evolution, sibling columns	Pathway Table schema. Iceberg types on Scale
Storage	Open Iceberg on Parquet you own	Your sinks. Iceberg I/O needs Scale
CDC	Log-based; fails closed if the dest cannot honour	Kafka / Postgres / Airbyte connectors. Iceberg is a sink
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	Pathway tables in-process. Downstream SQL is yours
Pricing	Free self-hosted engine	Community BSL (4 cores / 8 GiB). Iceberg is Scale.

What Pathway is good at

Incremental Python tables (joins, windows, persistence) without a JVM, on Kafka you already have, with the same code for stream and backfill. That is the product. Scale Iceberg read/write is why some teams land Parquet from Pathway instead of a Spark job. If the job is "this Pathway table into this Iceberg table," that is a real product.

Where the job is wider

Pathway is a dataflow engine. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight lake rows. Community will not open pw.io.iceberg. Iceberg date and maps are still missing on write. Postgres CDC is a connector, not fail-closed lake apply.

Cores, RAM, and a Scale key are the ops. Skippr will not replace a Pathway graph that already joins streams in Python. Skippr also will not run pw.run. Bytewax is a separate page.

If the job is "Pathway we already staff," Pathway is the narrower tool. If the job is live SQL on Iceberg you run, the Table API 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 Pathway if you want incremental Python tables, and Scale Iceberg I/O on that graph is enough.

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

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

Pathway alternative — Pathway vs Skippr ​

What Pathway is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Pathway alternative — Pathway vs Skippr

What Pathway is good at

Where the job is wider

Getting started

Which to choose