This article focuses on the technology, performance, and future planning of StarRocks' blazing-fast data lake analytics.
This article describes how to optimize the performance of the product features provided by the Enterprise Edition to help you efficiently access lake houses.
This article aims to solve the performance problems of offline data warehouses (daily and hourly) during production and usage.
This article reveals the key technologies of the data lake analytics engine in detail and uses StarRocks to help users understand the architecture of the system.
This short article discusses the rise and future of data lakes as a standard practice.
This article explains the continuous evolution of data warehouses, featuring offline/real-time integration and lake house.
This article explains how to deploy a data warehouse on Alibaba Cloud using AnalyticDB for MySQL service.
This article explains the four stages of lake house evolution within the Shanghai Shuhe Group.
This blog shows you how you can analyze your data stored in the cloud quickly, securely, and at low costs with Data Lake Analytics.
This article explains data lakes and how to build data lakes on Alibaba Cloud.
This article reviews Alibaba Cloud's enterprise-level cloud-native data lake solution launched during the double 11 festival and discusses its key benefits.
This article aims to give readers a deeper understanding of Alibaba Cloud Data Lake Formation (DLF) and Databricks DataInsight (DDI).
This article introduces the optimization and evolution of Flink Hudi's original mini-batch-based incremental computing model through stream computing.
This article explains the developmental stages of Alibaba’s data middle platform.
This article describes how to use ApsaraDB for PostgreSQL to achieve data lake analysis based on the foreign table object type of PostgreSQL.
This article introduces the best practices and cases for building, analyzing, developing, and governing cloud-native data lakes.
This article is a translation of the speech on how to quickly implement data warehouse and lake house based on MaxCompute.
Continuous Evolution and Development of Data Warehouse Architecture – Cloud Native, Lake house, Offline-Realtime Unification and SaaS Mode
This article introduces Fluid, an open source Kubernetes-native distributed dataset orchestrator and accelerator for data-intensive applications, and talks about the advantages of JindoRuntime.
This article introduces the exploration and practice of Mobvista in the field of cloud-native data lakes, as well as the architecture of StarLake.
