Qlik Talend Cloud alternative — Qlik Talend Cloud vs Skippr

Qlik Talend Cloud is Qlik's iPaaS. Stitch extract, Replicate-style CDC, Talend jobs, quality, and Qlik Open Lakehouse share one Cloud tenant. Four editions. Starter is scheduled SaaS and database extract into warehouses (minimum one-hour interval; no Private Link). Standard adds log CDC, hybrid agents, and Open Lakehouse: Iceberg in your AWS, an Adaptive Optimizer for compaction, and zero-copy mirrors into Snowflake, Databricks, BigQuery, or Redshift. Premium adds ELT and ETL transforms, column lineage, Spark batch, API jobs, a marketplace, and Trust Score. Enterprise adds SAP and mainframe. You buy capacity: data moved, job executions, duration, and Open Lakehouse core-hours. Dollar prices are quote. Stitch still has its own row packs (from 100 USD a month). Client-managed Qlik Data Integration and Talend Data Fabric remain for shops that will not go SaaS. New Stitch work is pointed at this suite.

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 edition gate. ELT into a warehouse is one path, not the product.

Feature	Skippr	Qlik Talend Cloud
Deploy	Single Rust binary, your VPC or on-prem	Qlik Cloud SaaS. Hybrid agent on Standard+. Client-managed QDI / Data Fabric still sold
Schema	In-stream evolution, sibling columns	Apply changes or Store changes (SCD2). Replicate-to-Iceberg onboard does not evolve schema
Storage	Open Iceberg on Parquet you own	Warehouse, or Open Lakehouse Iceberg in your AWS with Qlik's optimizer
CDC	Log-based; fails closed if the dest cannot honour	Log CDC from Standard. Starter is interval extract
Query	skipprd query on Iceberg ∪ WAL; history in any Iceberg engine	Destination or warehouse mirror after the task. Analytics Standard is bundled
Pricing	Free self-hosted engine	Capacity packs by edition. See Qlik. Stitch rows are a separate meter.

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What Qlik Talend Cloud is good at

The suite is the honest pitch. One tenant can land a Salesforce tap, a Postgres log, and a Talend quality rule without buying three logos. Open Lakehouse writes spec Iceberg and compacts it so Athena or Snowflake can read the same table. Replicate shops can keep the May 2026 engine, dump to S3, and let an onboard task build Iceberg without an upgrade. If you already pay Qlik for Analytics and want CDC plus a catalog in the same login, that is a real platform.

Where the job is wider

This is a managed integration cloud, not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight rows. Freshness is the edition: Starter waits an hour. Open Lakehouse compute is a meter. A Replicate onboard waits up to 15 minutes after a full load, will not take empty tables, and will not evolve schema. Delete-source-after-ingest means you cannot reload without regenerating files in Replicate.

Stitch and Talend Cloud are not the same product. _sdc_* columns, JSON flattening, and connector versions change on the move. Capacity overage can run to a multiple of the pack and bill in arrears. Quality, marketplace, and SAP sit behind Premium or Enterprise.

Skippr will not give you Trust Score, a Qlik marketplace, or SAP/mainframe extract. Skippr also will not replace a Qlik Analytics tenant. If the job is "Qlik-shaped CDC into Iceberg Qlik optimizes," Talend Cloud is the narrower tool. If the job is live SQL on Iceberg you run, Qlik Talend Cloud 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 Qlik Talend Cloud if you want Qlik's editions, Open Lakehouse, and a warehouse or Analytics tenant after the task is enough. Existing Stitch accounts should read the Stitch page.

Choose Skippr if you want one binary, no capacity pack, live SQL, and Iceberg files that stay yours. Skippr will not replace Talend Studio or Qlik Replicate.

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