Introducing ULTRON: A Real‑Time Data Warehouse Platform Powered by FlinkSQL

ULTRON is a real‑time data‑warehouse development platform created by the 360 commercial big‑data team, launched in version 1.0 after years of iteration on Flink, Kubernetes/YARN, and data‑warehouse productization. It adopts FlinkSQL as its core to provide end‑to‑end streaming analytics while integrating with offline Hive warehouses.

The platform solves the latency problems of traditional Hive‑based warehouses, which rely on batch ETL with T+1 or hourly schedules, by offering minute‑ or second‑level analytics for scenarios such as real‑time dashboards, fraud detection, and recommendation systems.

ULTRON delivers a one‑stop experience: data integration (Kafka ingestion, binlog collection), asset management (Kafka topics, storage resources), Flink cluster provisioning, data‑warehouse modeling, job development, testing, publishing, OLAP multi‑dimensional analysis (Druid, Presto, ClickHouse, TiDB), and data‑quality governance (metadata, lineage, model standards).

Key advantages include rapid Flink cluster deployment (often within a minute), automated handling of account, permission, quota, monitoring and alerting, and a unified IDE that abstracts underlying infrastructure complexities.

ULTRON is not an operations platform; it does not manage the installation, deployment, or optimization of the underlying infrastructure, nor does it provide higher‑level data‑science capabilities such as machine‑learning model serving.

Example FlinkSQL DDL for a Kafka source is shown below; ULTRON manages schema compatibility, parameter correctness, and secure credential handling through its metadata layer.

CREATE TABLE KafkaTable (
  `user_id` BIGINT,
  `item_id` BIGINT,
  `behavior` STRING,
  `ts` TIMESTAMP(3) METADATA FROM 'timestamp'
) WITH (
  'connector' = 'kafka',
  'topic' = 'user_behavior',
  'properties.bootstrap.servers' = 'localhost:9092',
  'properties.group.id' = 'testGroup',
  'scan.startup.mode' = 'earliest-offset',
  'format' = 'csv'
);

The article also outlines ULTRON's limitations, core design principles, resource‑pool abstraction (compute and storage), region‑aware asset registration, and a demo series that guides users through the complete real‑time data‑warehouse development workflow.