Apache Doris alternative — Apache Doris vs Skippr
Apache Doris is Apache-2.0 MPP analytics. FE plus BE (coupled, or compute-storage decoupled from 3.x). Latest core is 4.1.5 (16 Oct 2026). Iceberg is a catalog, not the storage engine: CREATE CATALOG … PROPERTIES ('type'='iceberg'). 4.1.5+ uses Iceberg SDK 1.11.0 (4.1.4 used 1.10.1; master tracks 1.12.0). Catalog types include REST, Hive Metastore, Glue, S3 Tables, JDBC (experimental since 4.1.0), DLF, and Hadoop. Doris can query Iceberg and write it: INSERT, INSERT OVERWRITE, UPDATE, DELETE, MERGE INTO, including branch writes. CDC into internal Unique Key tables is a load path: Streaming Job for MySQL/Postgres without an extra cluster (SQL Mapping Sync is exactly-once; Auto Table Creation Sync is at-least-once), Flink CDC plus the Doris connector when you already run Flink, Routine Load or the Kafka Connector for topics. Iceberg write-back is INSERT INTO SELECT from those internal tables or another catalog, not a WAL-to-Iceberg engine. There is no licence fee. You pay FEs, BEs, and disks or object storage. SelectDB Cloud is the commercial wrap. 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 | Apache Doris |
|---|---|---|
| Deploy | Single Rust binary, your VPC or on-prem | FE + BE cluster, or SelectDB Cloud |
| Schema | In-stream evolution, sibling columns | Doris DDL. Iceberg catalog DDL plus MERGE INTO |
| Storage | Open Iceberg on Parquet you own | Internal tablets. Iceberg via catalog read/write |
| CDC | Log-based; fails closed if the dest cannot honour | Streaming Job, Flink CDC, or Kafka load into Unique Key |
| Query | skipprd query on Iceberg ∪ WAL; history in any Iceberg engine | Doris SQL on internal tables or the Iceberg catalog |
| Pricing | Free self-hosted engine | Apache-2.0. Pay nodes. SelectDB Cloud is commercial. |
What Apache Doris is good at
MPP SQL on a warehouse cluster you run, Unique Key merge-on-write for CDC apply, and an Iceberg catalog that can both read the lake and write Parquet back. That is the product. Streaming Job without Flink is why some teams skip a second compute fleet. If the job is "this MPP warehouse, and Iceberg as a catalog," that is a real product.
Where the job is wider
Doris 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 Unique Key first; Iceberg is a later INSERT. Auto Table Creation Sync is at-least-once. Flink CDC still wants a Flink cluster.
FE/BE is the ops. Compaction, tablet count, Routine Load pause on max_error_number, and a catalog SDK pin (1.11.0 on 4.1.5). Skippr will not replace a Doris cluster that already serves BI. Skippr also will not run an FE. StarRocks is a separate page. Flink CDC is too.
If the job is "Doris we already staff," Doris 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.
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: ${APP_DB_PASSWORD}
database: app
tables: [orders, customers]
cdc_mode: snapshot_then_cdc
data_sinks:
lake:
AthenaIceberg:
warehouse: s3://my-iceberg-warehouse/
glue_database_name: analytics
athena_workgroup_name: primary
athena_results_s3_bucket: my-athena-results
region: us-east-1
schema_sink: schema_sinks.lake_schema
schema_sinks:
lake_schema:
AthenaIceberg:
warehouse: s3://my-iceberg-warehouse/
glue_database_name: analytics
athena_workgroup_name: primary
athena_results_s3_bucket: my-athena-results
region: us-east-1skipprd --workspace analytics --storage-mode local connect data-source postgres \
--pipeline orders \
--name app_db \
--host db.internal \
--user skippr_reader \
--password '${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_schemafrom 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 Doris if you want an MPP warehouse, Unique Key CDC apply, and 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 Doris.
Install from Install. Connector and query reference live in Developer Docs. For optional onboarding in your VPC, Enterprise Jumpstart or Contact.
