AWS Glue gives power to apply custom certificates for JDBC Connections

AWS Glue is an entirely organized extract, transform, and load service (ETL Service) which helps to make it easier and cost-effective to classify your data, clean it, enrich it, and transfer it securely between different data stores. AWS Glue contains a central metadata repository known as the AWS Glue Data Catalog. This Glue Data Catalog is an ETL engine which automatically produces Python or Scala code, and a flexible scheduler that takes care of dependency resolution, job monitoring, and retries. There is no infrastructure required to setup or manage as AWS Glue is serverless. Now custom certificates can be used in AWS Glue during JDBC connections to join to your data sources from Glue ETL jobs and crawlers. You may choose to apply custom certificates because you got a certificate from a third party supplier, or since the default certificates supported by AWS Glue do not fulfil your needs. Earlier, you were solely allowed to implement the default certificates offered by AWS Glue. Now this feature is accessible in every region where AWS Glue is available. Read the documentation to know further.

Now AWS Glue assists wheel files as dependencies for Glue Python Shell jobs

AWS Glue is an ETL service (extract, transform, and load) that is completely organized to make it easy to classify your data, polished it, enhance it, and transfer it accurately between different data stores. AWS Glue made up of a central metadata repository called as AWS Glue Data Catalog, an ETL engine that automatically creates Python or Scala code, and a flexible scheduler that handles dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. Earlier, you just allowed to add python dependencies with the help of egg files to AWS Glue Python Shell jobs. Now, with the help of wheel files, you can add python dependencies to AWS Glue Python Shell jobs, allowing you to get benefits of new potentials of the wheel packaging format. And now this feature is accessible in every AWS Region where AWS Glue is accessible. To get the complete list of AWS Region where AWS Glue is available, refer AWS Region page. To read more about this feature, read documentation.

AWS Glue offers FindMatches ML transform to remove duplicate data and search equivalent records in your dataset

AWS Glue is ETL service (extract, transform, and load) which is easy and cost-effective to classify your data, clean it, enrich it, and move it reliably between various data stores. AWS Glue is serverless, so there’s no infrastructure to set up or manage. AWS Glue includes a central metadata repository called as the AWS Glue Data Catalog, an ETL engine that automatically creates Python or Scala code, and a flexible scheduler which manages dependency resolution, job monitoring, and retries. Now AWS Glue can use to search equivalent records over a dataset with the help of new FindMatches ML Transform. FindMatches ML Transform is a custom machine learning transformation which aids you find equivalent records. By connecting the FindMatches transformation to your Glue ETL jobs, you can search connected products, places, suppliers, customers, and more. Besides, you can use this to remove duplicate data like to find customers who have signed up more than once, products that have been added inadvertently to your product catalog more than once, and so forth. You can instruct the FindMatches ML Transform your definition of a “duplicate” via examples, and it will utilize machine learning to search other possible duplicates in your dataset. This new feature AWS Glue ML Transforms is currently accessible in the US East (Northern Virginia), US East (Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Tokyo) AWS regions.

Now AWS Glue Feature Is Obtainable In South America (Sao Paulo) AWS Region

AWS Glue is an entirely organized ETL Service (Extract, Transform, Load) which is easy and cost-effective to classify your data, polish it, improve it, and shift it accurately within different data stores. AWS Glue made up of a central metadata repository called as the AWS Glue Data Catalog, an ETL engine which automatically creates Python or Scala code, and a flexible scheduler that manages dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. Now this AWS Glue feature is offered in the AWS South America (Sao Paulo) Region. AWS Glue crawls your data sources, recognizes data formats, and recommends schemas and transformations. AWS Glue can be used to execute serverless queries against your Amazon S3 data lake. AWS Glue automatically produces the code to run your data transformations and loading processes. AWS Glue execute your ETL jobs on Apache Spark environment. To get the entire list of region where AWS Glue is accessible, refer Region Table. And to know further about AWS Glue, read documentation

AWS Glue Is Obtainable In AWS EU (Stockholm) Region

AWS Glue is completely organized ETL Service i.e. Extract, Transform, Load. This service is simple for users to arrange and load their data for analytics. You can build and execute an ETL job with just some clicks in AWS Management Console. You can directly point AWS Glue to your data retained in AWS, and AWS Glue finds your data and keeps the related metadata in the AWS Glue Data Catalog. After data entered in catalog, its instantly searchable, queryable, and accessible for ETL. Now AWS EU (Stockholm) Region can access the AWS Glue feature. AWS Glue includes a central metadata repository i.e. AWS Glue Data Catalog. This is an ETL engine which automatically creates Python or Scala code, and a flexible schedule which manages dependency resolution, job monitoring, and retries. AWS Glue is serverless, so there’s no infrastructure to set up or manage. AWS Glue can utilize to design a data warehouse to manage, clean, validate, and format data. To read more information, refer AWS Glue. And to get complete list of regions where AWS Glue is accessible, refer the AWS Region Table.

Now Amazon Athena Is Accessible In GovCloud (US-East)

Amazon Athena is an interactive query service which is easy to use and simple to study data in Amazon S3 with the help of standard SQL. Athena is serverless, in order that there is no infrastructure to handle, and you charge exclusively for the queries which you execute. Just indicate to your data in Amazon S3, specify the schema, and begin querying with the help of standard SQL. Many outcomes are offered in few seconds. There is no necessity for complex ETL (Extract, Transform, Load) jobs to make your data for analysis with Amazon Athena. This helps for everybody with SQL expertise to rapidly study large-scale datasets. Athena is merged with AWS Glue Data Catalog, permitting you to build a unified metadata repository over different services, crawl data sources to locate schemas and occupy your Catalog with new and modified table and partition definitions, and retain schema versioning. Besides, you can utilized AWS Glue’s completely organized ETL potentials to change data or convert it into columnar formats to optimize cost and better performance. Now Amazon Athena is accessible in the AWS GovCloud (US-East) region and US East (Northern Virginia, & Ohio), US West (Oregon), AWS GovCloud, Europe (Ireland, Frankfurt, & London), and Asia Pacific (Singapore, Tokyo, Sydney, Seoul, & Mumbai) regions.