In previous articles, we saw how to connect with ODBC to SQL Server using the ODBC Data Source Administrator in Windows. This time, we will connect to Azure and export the data from one table in Azure to SQL Server on-premises using SSIS.
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In previous articles, we learn how to configure PostgreSQL ODBC drivers, how to configure ODBC drivers for Azure Database for MySQL, the differences between OLE DB, ODBC, and ADO.net, how to configure Linked Servers using ODBC DRIVER. This time we will use the ODBC Drivers to connect in SSIS.
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Azure SQL Database does not support native database backups. Therefore, you cannot use it to move from the Azure cloud to on-premises SQL Server. You can use the data-tier application BACPAC file format for exporting database schema and data from the Azure database. This BACPAC file is helpful to deploy on an Azure SQL Database, Managed Instance, and on-premises SQL Server.
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In this article, we are going to learn how we can migrate the tables with a foreign key to memory-optimized tables of the SQL database.
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In this series of articles, we will learn how to convert the disk-based table to an in-memory table of SQL Database.
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This article explains the different methods to move tables between different filegroup of SQL databases.
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The Bulk Copy Program (BCP) utility can move bulk data between SQL Server instances. You can export SQL Server data into BCP files. You can also use them for moving data from on-premises SQL Server instances to Azure SQL Database. The BCP files do not contain schema or the format information of your data. Therefore, you cannot use it as a database migration tool. However, it is adequate to import or export many rows. However, you need to create the table or use a format file to import data into a table.
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This article will walk you through the way to export data out of Azure SQL Databases in a compressed format using Azure Data Factory.
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In Azure, the Import/Export operation of the Azure SQL database is a vital part of the database migration methods. It is important to choose the most viable option as per the database migration strategy and business requirements. In addition, the applications that are configured with Azure SQL PaaS databases, the migration specialist could decide and identify several common scenarios where Azure PaaS database are scripted, copied, migrated, moved or backed up.
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In this article, we will explain how to install MongoDB on the Windows operating system, how to install and configure the ODBC driver and connector that allows us to import data from MongoDB to SQL Server using SSIS.
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In this article, you will see how to import data from JSON files and Power BI Rest API into the Power BI environment.
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In this article, I am going to explain how we can export the data of the on-premise MySQL database to Azure SQL database. This task can be performed in two phases.
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In the previously published article, we talked briefly about Hadoop, and we gave an overview of the SSIS Hadoop components added in the SQL Server 2016 release, and we focused on the Hadoop connection manager and the Hadoop file system task.
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In this article, I am going to explain how we can split the data within the excel file and upload it to the tables created on the Azure SQL database.
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In this article, we will explore various ways for scripting SQL Server database objects.
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The Data Flow Task is an essential component in SQL Server Integration Services (SSIS) as it provides SSIS ETL developers with an ability to conveniently extract data from various data sources; perform basic, fuzzy to advance data transformations; and migrate data into all kinds of data repository systems. Yet, with all its popularity and convenience, there are instances whereby the Data Flow Task is simply not good enough and recently, I got to experience such inefficiencies. To demonstrate some of the limitations of SSIS’s Data Flow Task, I have put together a random list of Premier League’s leading goal scorers for the 2019-2020 season.
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This article gives you an overview of BACPAC package and its usage in SQL Database data refresh (data import and export) using SQL Server management studio.
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This article explores the process of JSON data import in the SQL Server table using T-SQL and SSIS.
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This article shows the best way to import a copy of your MySQL database table to SQL Server using the SQL Server import data feature. We’ll demonstrate how to perform data import and export using a query with the assistance of SQL Server Management Studio.
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This article covers the following topics:
This article explores data import in SQL Server from a CSV file stored in the Amazon S3 SSIS bucket.
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XML (eXtensible Markup Language) is one of the most common formats used to share information between different platforms. Owing to its simplicity and readability, it has become the de-facto standard for data sharing. In addition, XML is easily extendable.
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This article explores the SSIS Multicast Transformation for creating different logical copies of source data.
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This article explores the SSIS Conditional Split Transform task to split data into multiple destinations based on the specified conditions.
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I have seen many organizations receive data from various sources and import into SQL Server. You might receive data in various formats and want to import into SQL Server. We can prepare a ETL (Extract-Transform-Load) process to import data into the SQL Server. In doing so, might receive data in a compressed file, which helps to send data over the network using a ZIP file format because it reduces the file size significantly. If we are receiving a ZIP file to import into SQL Server, we need to unzip it and then only we can import data. We might need to create a ZIP file as well from the existing files.
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