Alibaba Cloud Data Lake Analytics (DLA) is an interactive analytics service that utilizes serverless architecture. As a ready-to-use service, DLA does not require any prior setup of infrastructure or upfront management costs. You do not need to maintain instances in DLA, and service is billed based on actual use and needs. DLA uses SQL interfaces to interact with user service clients, which means it complies with standard SQL syntax and provides a variety of similar functions. DLA allows you to retrieve and analyze data from multiple data sources or locations such as OSS and Table Store for optimal data processing, analytics, and visualization to give better insights and ultimately guide better decision making.
Benefits
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Serverless
Designed as a ready-to-use service, DLA does not require any prior setup of infrastructure facilities, or incur massive upfront management costs. Upgrades to DLA can be performed with zero service downtime. DLA also supports elastic scaling to ensure the quality of services.
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Database-like User Experience
Complies with standard SQLs and supports a variety of functions, including JDBC and ODBC protocols and BI tools.
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Data Federation
Cloud native federation analytics across multiple data sources: OSS, PostgreSQL, MySQL (RDS), NoSQL (Table Store), etc.
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High-performance Analysis Engine
Leverages the new generation analysis engine XIHE and applies MPP and DAG technology to achieve high compression ratio, high scalability, and high availability.
Features
Server-less Big Data Analytics
Data Lake Analytics (DLA) utilizes a serverless architecture. This service is easy to manage and upgrade. You do not need to maintain instances when using DLA, which means maintenance costs are greatly reduced.
Cost Efficiency
DLA is billed based on actual usage, and you do not need to maintain instances. This means the service does not require long-term investment on data analysis.
Upgrade with Zero Service Downtime
Based on serverless architecture, you can upgrade DLA with zero service downtime for more agile and rapid product iteration.
Security and Reliability
Dedicated account management system, isolated virtual network, etc.
Secured Network
Fully secured and logically isolated service based on Virtual Private Cloud (VPC) technology
Fine-grained Access Control
Comprehensive authorization mechanism based on RAM/STS systems, scalable cryptographic key management based on Key Management Service (KMS)
Multisource Analytics
Data federation capabilities with built-in ETL
Built-in ETL
Transparent access to multiple data sources, including but not limited to object storage, NoSQL, RDBMS, with a unified user interface and ANSI SQL syntax.
Multisource Data Federation
Cloud native analytics across multiple data sources: OSS, PostgreSQL, MySQL, NoSQL(Table Store), etc.
Cloud Native Ecosystem
Database-like user experience with native support for a wide variety of SQL client tools and BI products
Support for MySQL Clients
Support MySQL client tools such as MySQL Workbench, DBeaver, etc.
Support for BI Products
Tightly integrated with QuickBI, Tableau, DataV, etc.
ANSI SQL Compatibility
Fully compatible with ANSI SQL:2003 syntax, comprehensive function support
Typical scenarios
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Data Analysis with OSS
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Table Store Data Analysis
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Support for Heterogeneous Data Sources
Data Analysis with OSS
Enables you to analyze data stored in OSS
DLA allows you to create tables, query raw data stored in OSS, and then display the query results through Quick BI.
Table Store Data Analysis
Enables you to analyze data stored in Table Store in real time
DLA offers an efficient and easy process for you to analyze large amounts of data stored in Table Store.
Support for Heterogeneous Data Sources
You can analyze data stored in Table Store and OSS
DLA supports heterogeneous data sources. It also enables you to perform association analysis by interworking with OSS and Table Store.
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