Integrate.io alternative — Integrate.io vs Skippr

Integrate.io is low-code SaaS for ETL, ELT, CDC, and reverse ETL. You draw a pipeline, they run it. Core is $1,999 a month: unlimited volumes, pipelines, connectors, and users, with a 60-second pipeline frequency. CDC reads Postgres, MySQL, SQL Server, and Oracle logs on that same cycle. A 14-day trial, a 30-day onboarding, and a dedicated solutions engineer are part of the pitch. Custom plans add HIPAA, tighter RBAC, and extra support. Formerly Xplenty.

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 $1,999 floor. ELT into a warehouse is one path, not the product.

Feature	Skippr	Integrate.io
Deploy	Single Rust binary, your VPC or on-prem	SaaS only. No self-hosted plane
Schema	In-stream evolution, sibling columns	Visual mapping plus schema-drift handling in their UI
Storage	Open Iceberg on Parquet you own	Destination warehouse. Pass-through processing in their cloud
CDC	Log-based; fails closed if the dest cannot honour	Log-based on a 60-second cycle for supported databases
Query	skipprd query on Iceberg ∪ WAL; history in any Iceberg engine	Warehouse after the load
Pricing	Free self-hosted engine	$1,999/month Core, custom above that. See their pricing.

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What Integrate.io is good at

A flat fee is the honest offer. You are not paying MAR, events, or per-connector minimums. Reverse ETL and CDC sit on the same bill as ingest. Analysts can stand up a pipeline without writing YAML. Reviewers like the onboarding and the support. If you already decided you will pay about two thousand a month for a managed canvas, and 60 seconds is live enough, that is a fair product.

Where the job is wider

$1,999 is the floor, not a starting credit. Light usage is cheaper on a usage-based tool, or on a binary you run. The connector set is smaller than Fivetran or Airbyte. Reviewers who like the canvas still mention thin connector error logs, a learning curve on the heavier transforms, and cluster-size limits on large jobs.

Integrate.io is cloud-only. There is no binary in your VPC. CDC is a 60-second cycle, not a query over in-flight WAL. There is no Iceberg ∪ WAL. Query waits for the destination.

Skippr will not give you Integrate.io's drag-and-drop canvas, reverse ETL destinations, or a dedicated solutions engineer. If the job is "one SaaS bill for ingest, CDC, and HubSpot activation," Integrate.io is the narrower tool. If the job is live SQL on Iceberg you run, Integrate.io 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 Integrate.io if you want one SaaS canvas for ingest, 60-second CDC, and reverse ETL, and a flat $1,999 is easier than watching MAR.

Choose Skippr if you want one binary, no monthly floor, 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.