Amazon Web Services, Inc. (AWS), an Amazon company, announced that AWS Glue and Athena are officially launched in the AWS China (Ningxia) Region operated by Xiyun Data. AWS Glue and Athena are serverless services, so customers do not need to manage the infrastructure. Users only pay for the computing resources they consume when performing ETL tasks.
AWS Glue is a fully managed data extraction transformation, and loading (ETL) service and metadata catalogue. It makes it easier for customers to prepare data, load data into databases, data warehouses, and data lakes for data analysis. With AWS Glue, data is ready for analysis in minutes.
When using a data lake architecture to implement a data analysis solution, customers usually spend 75% of their time on data integration tasks. They need to extract data from various data sources, normalize it, and load it into the data store. AWS Glue eliminates all the duplication of labour in the ETL operation infrastructure, allows the datasets in the Amazon S3 data lake to be discovered, can be used for querying and analysis, and greatly reduces the time for the ETL and data cataloguing phases in the analysis project, allowing ETL Made it easy.
After AWS Glue crawls data from the data source selected by the customer it will automatically identify the data format and schema build a unified data catalogue, and provide customers with a central view of the selected data. This makes it easy for customers to store, retrieve and manage all data across a variety of data without having to move them manually. When a customer identifies a data source (such as a database table) and a data target (such as a data warehouse) from a data catalogue, AWS Glue will match the corresponding pattern to generate a customizable, reusable, portable, and shareable data transformation Code. Developers can schedule any number of ETL jobs, and AWS Glue manages the rest of the work, automatically enabling or disabling computing resources based on customer ETL workloads. By simplifying the process of creating ETL jobs, AWS Glue enables customers to build scalable and reliable data preparation platforms. These platforms can span thousands of ETL jobs and have built-in dependency resolution, scheduling, resource management, and monitoring capabilities.
“AWS ‘scalable and reliable cloud storage, coupled with our extensive analytics services, makes it easier than ever for customers to collect, store, analyze and share data,” said Zhang Wenhua, vice president of AWS and executive director of Greater China, “With the official launch of AWS Glue in the AWS China (Ningxia) region operated by Xiyun Data, customers in the China region can easily transmit and process data from any number of data sources, integrate data into the data lake, and choose from a variety of AWS Analysis Services quickly started analyzing all data. Currently, several Chinese customers, including Derby Software package, Jiayun Data, Softwood Software, and FunPlus are using AWS Glue to solve their complicated data challenges.
Amazon Athena is an interactive query service that allows customers to easily analyze data in Amazon Simple Storage Service (Amazon S3) using standard SQL language. Athena can automatically scale and execute queries in parallel, so you can get query results quickly even for large data sets and complex queries.
AWS provides analytics services such as Amazon Redshift and Amazon Elastic MapReduce (Amazon EMR), enabling companies of all sizes to analyze petabytes of data. With Amazon Redshift, customers can perform complex queries on large-scale structured data and get super-fast performance. For unstructured data, Amazon EMR uses popular distributed frameworks, such as Apache Spark, Presto, Hive, and Pig, to process and analyze large amounts of data across multiple dynamically scalable clusters, quickly and economically. Although these services are scalable and powerful enough to handle large and complex big data applications, many customers also want to be able to quickly query data on Amazon S3, such as weblogs, clickstreams, raw log files, etc. Without having to open, configure, and manage a Hadoop cluster or data warehouse. Using Athena to analyze data in Amazon S3 is now as easy as writing SQL queries. Athena uses Presto, which fully supports standard SQL, and can handle a variety of standard data formats, including CSV, JSON, ORC, and Parquet. Because Athena uses computing resources in multiple Availability Zones to execute queries, and uses Amazon S3 as the underlying data store, it has high availability and durability. Data is stored redundantly in multiple infrastructures, and is on each infrastructure. On multiple devices.
“Customers typically raise a question with us if we can make it easy and simple for them to perform queries on data and information in the Amazon S3 data lake without having to worry about configuring managing servers and clusters, said ” Zhang Wenyu vice president of AWS and executive of bigger China” Now, we are very happy to launch Amazon Athena in the AWS China (Ningxia) region operated by Xiyun Data in response to the needs of AWS Chinese customers. Amazon Athena does not require management infrastructure at all and anyone who can write SQL queries can be cost-effective Way to quickly analyze their data in Amazon S3. ” China And Pakistan both countries have placed significant bond and both countries regularly exchange their goods and technology so it may Amazon Web Services Glue and Athena will officially be launched in Pakistan too so that Pakistan software export board and software companies in Pakistan will provide more ease for local Public.
You Must Also Read