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Last Updated: Jun 06, 2019


Data Lake Analytics (DLA) is a serverless cloud native interactive cloud native query and analytics service. For enterprise users edition users, the service is made available on abilling method is Pay-As-You-Go. Due to itsLA basis serverless architecture, DLA alsocompletely removes the need for server maintenance requirementswith ZERO maintenance effort. Key benefits of DLA, include include but are not limited to, but not limited to instant startup, transparent upgrades, and elastic Quality of Service (QoS).

Database Experience

DLA offers standard SQL interface, with that has outstanding SQL compatibility and comprehensive built-in functions. DLA employs standard Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC) technologiesy to provide users quick service access, while lowering application transformation and migration costs. Based on JDBC/ODBC connectivity, users are granted with fast and convenient service access, and low migration cost. Meanwhile, compatibility with Business Intelligence (BI) tools integration with BI product enables DLA to turn turn big data into consumable data insights and visualizations. With its strong database experienceintegration capabilities, DLA helps can help customers accelerate their cloud-based migrationdata analytics processes.

Heterogeneous Data Sources

DLA enables complex analytics analysis of different data sources and formats. Not only can for data coming from different sources with various formats. users Not only user can leverage DLA to analyze data stored on Alibaba cloud Cloud OSS and Table Store respectively, but they can also integrate, they can join the the se services analysis results and thusto generate new data insights.

High-Performance Engine

DLA Ffully leveragesing Massive Parallel Processing (MPP) and Directed Acyclic Graph (DAG) architecture, providing to provide vectorized execution optimization, pipelined operator piplelined execution optimization, multi-tenancy resource allocationresource isolation, and priority scheduling.