New Features

Supports Near Real-time Data Ingestion from Message Queue for Apache Kafka

Aug 09 2021

The Data Lake Analytics (DLA) lakehouse solution allows you to build a data warehouse by ingesting data from Message Queue for Apache Kafka into a data lake within T+10 minutes. The ingested data is stored in the Apache Hudi format. The DLA lakehouse solution supports capabilities, such as partition management and small-file merging.
Content

Target customers: users who work in various fields, such as gaming, online education, and Internet of vehicles (IoV). The DLA lakehouse solution is suitable for different types of analytics, such as query analytics, federated analytics, and offline analytics of data warehouses or data lakes based on behavioral logs and event tracking logs. Features released: The DLA lakehouse solution allows you to build a data warehouse by ingesting data from Message Queue for Apache Kafka into a data lake within T+10 minutes. The ingested data is stored in the Apache Hudi format in Object Storage Service (OSS). This solution supports capabilities, such as schema inference, partition management, and small-file merging. This solution reduces the storage cost and simplifies data warehousing by ingesting data from Message Queue for Apache Kafka into a data lake. To build a data warehouse, you need only to specify virtual cluster parameters and use your mouse to click related buttons or menu items. The DLA lakehouse solution is suitable for different types of analytics, such as query analytics, federated analytics, and offline analytics of data warehouses or data lakes based on behavioral logs and event tracking logs.

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