Appearance

Book a call

FME alternative — FME vs Skippr ​

FME is Safe Software's spatial ETL. You draw a workspace in FME Form (transformers, readers, writers, breakpoints). You deploy it on FME Flow: schedule, event trigger, or a no-code web app. FME Flow Hosted is that server on AWS, managed by Safe. FME Realize puts the result in AR on iOS. A subscription is quote and is supposed to include Form, Flow, Flow Hosted, and Realize. Hosted instance list (USD, unlimited engines) is Standard 12,000 a year or 2.40 an hour (2 cores, 8 GB), Professional 20,000 or 4.00 (4 cores), Select 30,000 or 6.00 (8 cores), Premium 40,000 or 8.00 (16 cores), Enterprise 75,000 or 15.00 (48 cores). Annual plans cap included transfer and storage; hourly adds disk, backup, and egress. FME 2026.3 shipped an Apache Iceberg reader (S3, Azure, GCS, Glue). Docs still mark it Technical Preview and say not for production. The Iceberg writer is planned. This is format conversion and geometry, not a Streamhouse.

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 Form canvas. ELT into a warehouse is one path, not the product.

FeatureSkipprFME
DeploySingle Rust binary, your VPC or on-premForm on a desktop. Flow or Flow Hosted to run it
SchemaIn-stream evolution, sibling columnsFeature types and transformer ports
StorageOpen Iceberg on Parquet you ownWriter you picked. Iceberg writer is not shipping
CDCLog-based; fails closed if the dest cannot honourEvent-triggered Flow jobs. Not log CDC
Queryskipprd query on Iceberg ∪ WAL; history in any Iceberg engineTarget after the workspace. No lake SQL in FME
PricingFree self-hosted enginePlatform subscription is quote. Hosted instances from 12,000 USD/year.

What FME is good at ​

A shapefile, a CAD drawing, and a PostGIS table in one workspace. That is the product. Thousands of spatial and tabular formats, on-the-fly reprojection, and a transformer library GIS teams already know. Flow can fire when a file lands. If the job is "this geometry into that CRS and that file," that is a real product.

Where the job is wider ​

FME is a workspace runner. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight rows. The workspace ends; then you open the file.

Iceberg is a reader in preview. Safe's own docs say do not put it in production. There is no writer. Hosted hourly looks cheap until the instance is up all month and egress is extra. Form is required to author; Flow alone will not draw the graph.

Skippr will not reproject a shapefile. Skippr also will not run an FME workspace. If the job is "spatial formats and transformers," FME is the narrower tool. If the job is live SQL on Iceberg you run, FME 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.

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 FME if you need spatial format conversion and transformers, and a file after the workspace is enough.

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

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