Sling alternative — Sling vs Skippr

Sling is a Go CLI for extract-load between databases, files, and APIs. One binary. YAML (or JSON) in Git. Wildcard table copies, custom SQL as a stream, flatten nested columns, pre and post SQL. The core CLI is free (GPLv3). CLI Pro is 79 USD a month for API sources, parallel streams, delete capture, hooks, and ODBC. 149 USD a month adds log-based CDC and schema migration (keys, indexes, constraints). Platform is a separate UI: free, 99, or 249 USD a month flat. A 7-day Pro trial, no card.

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. CDC is in the engine, not a Pro SKU. ELT into a warehouse is one path, not the product.

Feature	Skippr	Sling
Deploy	Single Rust binary, your VPC or on-prem	Single Go binary. Platform agents in your VPC
Schema	In-stream evolution, sibling columns	Detects schema. `add_new_columns` / type adjust. Full key migration on Pro 149
Storage	Open Iceberg on Parquet you own	Destination database or files (CSV, Parquet, JSON, Excel, S3 / GCS / Azure)
CDC	Log-based; fails closed if the dest cannot honour	Incremental and delete capture on Pro 79. Log CDC on Pro 149
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	Destination after the load
Pricing	Free self-hosted engine	Free CLI. Pro 79 or 149 USD a month. See their pricing.

What Sling is good at

A binary you can curl and a 12-line YAML is a fair first hour. Database to warehouse, CSV to Postgres, S3 Parquet in, wildcard schema.* out. Reads existing dbt connection strings. No MAR. For small-to-medium copies a data engineer already knows how to cron, that is a real product. Platform adds a UI if the team will not live in Git.

Where the job is wider

The free CLI is extract-load. Log CDC, schema migration, and API sources sit on Pro. One Pro subscription is two tokens (prod and dev) per team. Another team, another bill. Connector count is tens of databases and files, plus REST specs, not Fivetran's SaaS catalog. Reviews that like the YAML still note a smaller community.

Sling is ELT. It is not a Streamhouse. There is no Iceberg ∪ WAL. Query waits for the destination. GPLv3 is not a reason to skip it; it is a reason to read the licence before you embed it.

Skippr will not give you Sling's Excel source, dbt-conn import, or their Platform UI. If the job is "copy these tables tonight from Postgres to Snowflake," Sling is the narrower tool. If the job is live SQL on Iceberg you run, Sling 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 Sling if you want a Go CLI and YAML for database and file copies, and Pro CDC is enough.

Choose Skippr if you want one binary, CDC without a Pro SKU, live SQL, and Iceberg files that stay yours.

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

Sling alternative — Sling vs Skippr ​

What Sling is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Sling alternative — Sling vs Skippr

What Sling is good at

Where the job is wider

Getting started

Which to choose