A software project should have a database. You can use SQL or no-SQL database. You choose SQL when you work with structured data that should have specific constraint and schema. You choose no-SQL if you prefer a simple and high-performance data access. Visual Studio officially support both databases. On this article, we discuss what database option that we have and how to choose the correct option.
SQL Database
You have a lot of options to deploy SQL-based database. We will focus on two main approaches in this post.
SQL database that can be embedded in the application.
If you build a desktop software that run on top of Windows. You can use Microsoft Access.
If you build a web that run on top of Windows based hosting. You can use SQL Compact Edition. You can install the extension on the visual studio marketplace
SQL Database that should deployed separately in the application.
If you build a web that build the database from the scratch or existing SQL script, you can use the SQL Database Project
If you build a web that use code-first design, you can use Code First to a New Database - EF6 | Microsoft Docs
You can deploy both database to Microsoft Azure and your on-premises environment. You can do the deployment process through SQL Server Management Studio or Visual Studio Server explorer or publish profile.
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No SQL Database
Unfortunately, there is no built-in support for No SQL Database. This is because the NO SQL database is simple enough to install and to implement by using NuGet package manager.
My first choice is to use Mongo DB. You can install the extension of Mongo DB Mongo DB Tools - Visual Studio Marketplace
If you want to deploy into the cloud you can use Cosmos DB. You can visit NuGet Gallery | Microsoft.Azure.DocumentDB 2.13.1
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The Fun Fact about the data
When we build anything, we use data. Start from structured data, unstructured data, and semi-structured data we store the data to retrieve it as information and knowledge. Despite of the data usage, we know that the data in our life is growing. And when we can't store the data in the local storage the cloud is the answer. The question is how we store and manage the data in the cloud. This article will discuss how we store and analyze the data in the cloud era. You can read the data concept here
The Data Store
You can store the data in two types relational data or non-relational data.
In non-relational data you will have Azure Cosmos DB, File, Blob, and many more. You can learn more here
In relational data you will have the power of SQL Azure, as well as MySQL, Maria DB and any others database. You can learn more here.
If you need high volume transaction without than the Non-relational data is for you. However, for small and tight relation between data you need the relational database such as SQL Server. You can learn more the consideration here.
The Data Analytics
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After the data is stored, you can analyze the data for more useful manner. This step knowns as analytics. According to Microsoft they have several products which are?
Azure Data Factory who take any data and convert it into format that you need. The ETL process heavily happen in this Azure Data Factory
Azure Data Lake who store raw data to ready to retrieve as fast as it can. Azure Data Lake is the main storage for Azure Data Factory
Azure Databricks is a tool to provide big data processing, streaming, and machine learning. It can use data lake as a data source
Azure Synapse Analytics is an analytics engine. It is designed to process large amounts of data very quickly. Azure Synapse Analytics supports two computational models: SQL pools and Spark pools.
Azure Analysis Services enables you to build tabular models to support online analytical processing (OLAP) queries. You can combine data from multiple sources from the data lake, cosmos DB, and off course SQL Azure
Azure HDInsight is a big data processing tool based on well-known platform Hadoop.
You can learn more about analytics here. After you have analytics you can pull it into dashboard or report by using Power BI.
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