One open-source tool that helps teams track, version, and deploy database schema changes is Liquibase. It executes database scripts sequentially, allows for the automatic creation and execution of rollback scripts for failed updates, and provides an easy way to use the same scripts and apply them to different types of databases.
This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,
In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.
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If you are a back-end developer, you are often faced with having to migrate your database schema with each new release.
The framework called Liquibase can make it easier for you when you need to upgrade your database schema.
In this article, I’ll explain how Liquibase can be used in a Java project, with Spring/Hibernate, to version the database schema.
Liquibase works with Changelog files (the list of all the changes, in order, that need to execute to update the database).
There are 4 supported formats for these Changelogs: SQL, XML, YAML, and JSON.
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Finding the right database solution for your application is not easy. At iQIYI, one of the largest online video sites in the world, we’re experienced in database selection across several fields: Online Transactional Processing (OLTP), Online Analytical Processing (OLAP), Hybrid Transaction/Analytical Processing (HTAP), SQL, and NoSQL.
Today, I’ll share with you:
I hope this post can help you easily find the right database for your applications.
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Category: Tutorials | Tags: Cassandra, Columns, Database, Database Management, Database Structure, DB2, Document Stores, Dynamic Schema, Extensible Record Stores, Graph Stores, JSON, Key-Value, MSSQL, Multi-Row, MySQL, Node, Node Relationship Node, Non-Relational Databases, NoSQL, NoSQL Model, Query, Rows, Scalability, Schema Free, SQL, Stores, Tables, Wide-Column
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A NoSQL or a NoSQL Database is a term used when referring to a “non SQL” or “not only SQL” database. NoSQL databases store data in a different format than a traditional relational database management systems. This is why NoSQL is often associated with the term “non-relational” database. Simply put, NoSQL databases are modern databases with high flexibility, blazing performance, and built for scalability. These databases are used when you require low latency and high extensibility while working with large data structures. The versatility of NoSQL is due to the nature of as being unrestricted in comparison to relational databases models such as MySQL or DB2.
There are multiple differences between SQL and NoSQL database types. In the table below, we will compare some of the most critical variations.
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The pandemic has brought a period of transformation across businesses globally, pushing data and analytics to the forefront of decision making. Starting from enabling advanced data-driven operations to creating intelligent workflows, enterprise leaders have been looking to transform every part of their organisation.
SingleStore is one of the leading companies in the world, offering a unified database to facilitate fast analytics for organisations looking to embrace diverse data and accelerate their innovations. It provides an SQL platform to help companies aggregate, manage, and use the vast trove of data distributed across silos in multiple clouds and on-premise environments.
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