Denodo alternative — Denodo vs Skippr

Denodo Platform 9 is a logical data warehouse. Virtual DataPort sits in front of databases, SaaS, APIs, and object storage and answers SQL without copying the row first. The 9.5 datasheet lists Parquet, Delta, and Iceberg as lake formats. Lakehouse Accelerator plus Iceberg caching is the new acceleration path: a Presto-based MPP on Velox reads the lake, and Iceberg is the cache so you compact less. Denodo Scheduler and remote tables exist when you do want a physical move. Lineage goes out through Governance Bridge (Collibra, Purview, OpenLineage). This is federation, not CDC. AWS Marketplace consumption tiers (12 months) are Team at 180,000 USD (one server, up to 8 cores, 100 data products, 7.5 TB/year), High Availability at 360,000 USD (225 products, 25 TB/year), and Business Critical at 900,000 USD (750 products, 75 TB/year). Azure Enterprise Plus starts at 32.21 USD an hour for four cores, compute extra. On-prem and BYOL are quote.

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 Virtual DataPort. ELT into a warehouse is one path, not the product.

Feature	Skippr	Denodo
Deploy	Single Rust binary, your VPC or on-prem	VDP on-prem, in your cloud account, or Denodo-managed
Schema	In-stream evolution, sibling columns	Derived views and data products in the marketplace
Storage	Open Iceberg on Parquet you own	Sources stay put. Iceberg is a source or a cache
CDC	Log-based; fails closed if the dest cannot honour	Not a CDC product. Someone else lands the change
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	Federated SQL through VDP. MPP for lake scans
Pricing	Free self-hosted engine	Consumption (products + TB) or hourly cores. See Marketplace.

What Denodo is good at

A join that should not become a pipeline. That is the product. Point VDP at Oracle, a SaaS API, and an Iceberg folder, publish a data product, and leave the sources where they are. Accelerator plus Iceberg cache is why lake scans do not always need a second warehouse. If the job is "logical access without another copy," that is a real product.

Where the job is wider

Denodo is a virtualization plane. It is not a Streamhouse. There is no Iceberg ∪ WAL that Skippr wrote. There is no skipprd query on in-flight CDC. Iceberg in 9.5 is a format Denodo can read and a cache it can write. The change still has to arrive somehow.

Consumption math is the ops. Team is 100 products and 7.5 TB retrieved per year. Cross either line and you are on the next tier or a private offer. Hourly Azure still bills the VM under the 32.21 USD software hour.

Skippr will not federate Oracle and Salesforce in one view. Skippr also will not replace Denodo Scheduler. If the job is "query sources in place," Denodo is the narrower tool. If the job is live SQL on Iceberg you run, Denodo 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 Denodo if you want federated SQL over sources you will not copy, and a logical data product is enough.

Choose Skippr if you want one binary, live SQL, and Iceberg files that stay yours. Skippr will not virtualize Oracle in place.

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

Denodo alternative — Denodo vs Skippr ​

What Denodo is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

Denodo alternative — Denodo vs Skippr

What Denodo is good at

Where the job is wider

Getting started

Which to choose