StarRocks alternative — StarRocks vs Skippr

StarRocks is Apache-2.0 MPP analytics. FE plus BE, or shared-data on object storage. Latest release is 4.1.7 (26 Oct 2026). Iceberg catalogs have been queryable since 2.4. Writes landed in 3.1: INSERT INTO and INSERT OVERWRITE into Parquet Iceberg only. Partition columns cannot be NULL. DELETE FROM Iceberg is documented from 4.1. TRUNCATE TABLE empties an Iceberg table. CDC into internal Primary Key or Unique tables is Stream Load, Routine Load (Kafka), Broker Load, or Flink CDC plus the StarRocks connector (Stream Load 2PC). Multi-table transactional Stream Load in 4.0.16+ dispatches all table channels before waiting, which shortens CDC commits that fan out. Iceberg is a catalog sink after that, not the CDC dest. There is no licence fee. You pay FEs, BEs, and disks or object storage. CelerData (PhoenixAI Cloud) is the commercial wrap; AWS Marketplace lists CelerData Enterprise at 175 USD per CPU core per month on a one-month contract (12/24/36-month contracts discount). This is 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. No FE. ELT into a warehouse is one path, not the product.

Feature	Skippr	StarRocks
Deploy	Single Rust binary, your VPC or on-prem	FE + BE, shared-data, or CelerData Cloud
Schema	In-stream evolution, sibling columns	StarRocks DDL. Iceberg catalog; writes Parquet only
Storage	Open Iceberg on Parquet you own	Internal tablets. Iceberg via catalog
CDC	Log-based; fails closed if the dest cannot honour	Stream Load / Routine Load / Flink CDC into internal tables
Query	`skipprd query` on Iceberg ∪ WAL; history in any Iceberg engine	StarRocks SQL on internal tables or the Iceberg catalog
Pricing	Free self-hosted engine	Apache-2.0. Pay nodes. CelerData Marketplace from 175 USD/core-month.

What StarRocks is good at

Low-latency SQL on a warehouse cluster, Primary Key upserts for CDC apply, and an Iceberg catalog that can query the lake and append Parquet. That is the product. Shared-data mode is why some teams put BE cache in front of S3 instead of local replicas. If the job is "this MPP warehouse, and Iceberg as a catalog," that is a real product.

Where the job is wider

StarRocks is a warehouse. It is not a Streamhouse. There is no Iceberg ∪ WAL. There is no skipprd query on in-flight lake rows. CDC lands internal tables first. Iceberg INSERT will not write ORC or Avro. Partition NULL is rejected. DELETE on Iceberg needs 4.1.

FE/BE is the ops. Compaction, tablet count, Stream Load labels, and a CelerData bill if you are not self-hosting. Skippr will not replace a StarRocks cluster that already serves BI. Skippr also will not run an FE. Apache Doris is a separate page. Flink CDC is too.

If the job is "StarRocks we already staff," StarRocks is the narrower tool. If the job is live SQL on Iceberg you run, the warehouse 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 StarRocks if you want an MPP warehouse, Primary Key CDC apply, and Parquet Iceberg as a catalog on that cluster.

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

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

StarRocks alternative — StarRocks vs Skippr ​

What StarRocks is good at ​

Where the job is wider ​

Getting started ​

Which to choose ​

StarRocks alternative — StarRocks vs Skippr

What StarRocks is good at

Where the job is wider

Getting started

Which to choose