Census alternative — Census vs Skippr

Census is reverse ETL. Fivetran announced the acquisition in May 2025. From 1 Feb 2026 the product is Fivetran Activations: SQL-modeled warehouse rows into Salesforce, HubSpot, ads, and the rest of the operational tools. Iceberg is a source when a supported engine can query it (Athena, Trino, Snowflake, BigQuery, Databricks, and others on Fivetran's list), not a lake writer. Activations bills Monthly Active Rows: unique sync keys inserted, updated, or deleted, counted once per activation per month, on their own declining consumption curve. Free plan caps Activations at 3,500 MAR/month (Connections get a separate 500,000 MAR). Each new activation has a 14-day trial. This is warehouse-out, 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. Skippr will not sync Salesforce. ELT into a warehouse is one path, not the product.

Feature	Skippr	Census (Fivetran Activations)
Deploy	Single Rust binary, your VPC or on-prem	Fivetran Cloud
Schema	In-stream evolution, sibling columns	Warehouse SQL / models. Mapping in the activation
Storage	Open Iceberg on Parquet you own	Reads your warehouse. Writes the SaaS dest
CDC	Log-based; fails closed if the dest cannot honour	Not CDC. Diff of modeled rows out to an app
Query	skipprd query on Iceberg ∪ WAL; history in any Iceberg engine	The warehouse you already query. Activations is the push
Pricing	Free self-hosted engine	MAR. Free: 3,500 activation MAR/month.

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What Census is good at

Putting a modeled warehouse column onto a Salesforce field on a schedule, without writing the Salesforce client. That is the product. Audience Hub and the Fivetran invoice (one contract with Connections) are why some teams collapsed a second reverse-ETL vendor. If the job is "this gold table into this CRM," that is a real product.

Where the job is wider

Census is reverse ETL. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight lake rows. Iceberg is only in play if Athena or another listed engine already serves the table. Postgres CDC still lands somewhere else first. Skippr will not replace an activation into HubSpot.

MAR, the Fivetran workspace, and warehouse query cost for the models are the ops. Skippr will not run Activations. Fivetran ELT is a separate page. Hightouch, RudderStack, and Segment are separate pages.

If the job is "warehouse into Salesforce," Census is the narrower tool. If the job is live SQL on Iceberg you run, reverse ETL 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

CLI

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")

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 Census / Activations if you want modeled warehouse rows in the CRM, and MAR on Fivetran's bill is acceptable.

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

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