The Young DBA

Hello friends, Many MySQL developers and administrators are waiting since long for mysql 8.0 on AWS RDS.  Now Amazon RDS for MySQL started supports MySQL Community Edition major version 8.0 in all AWS Regions. Please upgrade your instance to test new product performance. MySQL 8.0 is the latest major version release and offers new query functionality and enhancements for better performance, reliability, security, manageability, and international and mobile support. Here is MySQL 8.0 Version Summary: MySQL Document Store. JSON enhancements. New Window functions. New Common Table Expression & Recursive CTE. Better with documents and JSON. New Database Roles. Index Hiding, a.k.a “Invisible” Indexes Configuration Persistence. Unicode UTF-8 Encoding. InnoDB NO WAIT & SKIP LOCKED. Thanks for reading Plz dont forget to like Facebook Page.. YoungDBA on Facebook

Transformation in technologies creating lots of changes in every related area. Artificial Intelligence, Machine Learning and Data-Science created a new kind of concept   in data platform, that is " Data Virtualization " .   By name it look like it might be related to server or network, but it is concept and logical method of data management. Data virtualization is the method of manipulating data from various sources to develop a common, logical and virtual view of information so that it can be accessed by front-end solutions such as applications, dashboards and portals without having to know the data's exact storage location. What are the benefits of Data virtualization? ·          Data virtualization increases revenues. ·          Data virtualization lowers costs. ·          Data virtualization reduces risks ·          It is much faster way to manage data. ·          It complements traditional data-warehouse ·          It maximize performance of

AWS documentation also says horizontal physical partitioning of large table data is best practices instead keeping all in one physical file. There are advantages and disadvantages to using InnoDB file-per-table tablespaces, depending on your application. To determine the best approach for your application, go to InnoDB File-Per-Table Mode in the MySQL documentation. We don't recommend allowing tables to grow to the maximum file size. In general, a better practice is to partition data into smaller tables, which can improve performance and recovery times. One option that you can use for breaking a large table up into smaller tables is partitioning. Partitioning distributes portions of your large table into separate files based on rules that you specify. For example, if you store transactions by date, you can create partitioning rules that distribute older transactions into separate files using partitioning. Then periodically, you can archive the historical transaction data th

This is the new function introduced with 2016 version of SQL Server. This is used to cast value from its existing data type to a specified target data type. This occurs only if the operation is successful. It returns NULL if the conversion fails. TRY_CAST is an extended version of the CAST function. Query SELECT CAST ( 'Tech-Recipes' as INT ) as CastExample ; result Msg 245 , Level 16 , State 1 , Line 2 Conversion failed when converting the varchar value 'Tech-Recipes' to data type int . query SELECT CAST ( '12' as INT ) as CastExample ; result 12 SELECT TRY_CAST ( 'Tech-Recipes' as INT ) as CastExample ; Result NULL SELECT TRY_CAST ( '20' as INT ) as CastExample ; Result 20

This is new built-in table-valued function introduced in sql server 2016. STRING_SPLIT that splits the provided input string by a specified separation character and returns the output separated values in the form of table. This is usefull-function that you might always use userdefined long and unoptimized function in most applications. Now sql server have built in function to split the text. Query SELECT * FROM STRING_SPLIT('Suman,Satyam,Shivam',',') Result Suman Satyam Shivam Thanks for reading Plz dont forget to like Facebook Page.. https://www.facebook.com/pages/Sql-DBAcoin/523110684456757

Temporal, or system-versioned tables which was introduced in SQL Server 2016, allow us to go back in time and see what the data in table looked like at that point in time. We can say a system-versioned temporal table is a type of user table designed to keep a full history of data changes and allow easy point in time analysis. This type of temporal table is referred to as a system-versioned temporal table because the period of validity for each row is managed by the system. What are the usage of Temporal Tables ? The most common business uses for temporal tables are: Slowly changing dimensions. The temporal tables provide a simpler way to querying data that is current for a specified period of time, such as time slicing data, that well-known problem on Data Warehousing databases. Data Auditing. The temporal tables provide an audit trail to determine when data was modified in the “parent” table. Temporal tables allow you to query data as it was at a particular point in time to

A running application can have multiple database integrated environment to send receive data. Some time multiple database of Postgres or sometimes other database like sql server/mysql/mongodb. Every database have different-different feature to integrate. Like sql server have Linked Server, mysql have Data federation Postgres have foreign data wrapper. This post is related to Postgres's foreign data wrapper. What is foreign data wrapper in Postgres ? How to access table from other database in Postgres ? Postgres have a  different feature which lets you to create a foreign data wrapper inside Postgres, which lets you feel the object of current connected database. It will help to create object that will part of foreign data or database. So we can easily integrated data. This feature is called foreign data wrapper. What are the components of foreign data wrapper ? 1. Foreign Data wrapper Extension { file_fdw , postgres_fdw } 2. Foreign database server location 3. User Mappi