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Waiting is over MySQL 8.0 is Available on AWS RDS

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” IndexesConfiguration Persistence.Unicode UTF-8 Encoding.InnoDB NO WAIT & SKIP LOCKED.
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What is Data virtualization

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 overall information system environment. ·Data virtualization automatically enables self-service BI…

MySQL Table Partitioning over cloud (Google & AWS)

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 that does…

what is TRY_CAST in sql server

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

SELECTCAST('Tech-Recipes'asINT)as CastExample; result Msg 245,Level 16,State 1, Line 2 Conversion failed when converting the varchar value 'Tech-Recipes'to data typeint.
query SELECTCAST('12'asINT)as CastExample;
result
12
SELECT TRY_CAST('Tech-Recipes'asINT)as CastExample;
Result
NULL
SELECT TRY_CAST('20'asINT)as CastExample;
Result

20

What is String_Split in sql server

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

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