Importing excel into sql

There are many articles about writing code to import an Excel file, but this is a manual/shortcut version:

If you don’t need to import your Excel file programmatically using code, you can do it very quickly using the menu in SQL Server Management Studio (SSMS).

The quickest way to get your Excel file into SQL is by using the import wizard:

1. Open SSMS (SQL Server Management Studio) and connect to the database where you want to import your file into.

2. Import Data: in SSMS in Object Explorer under ‘Databases’, right-click the destination database, and select Tasks, Import Data. An import wizard will pop up (you can usually just click Next on the first screen).

   

3. The next window is ‘Choose a Data Source‘. Select Excel:

• In the ‘Data Source’ dropdown list, select Microsoft Excel (this option should appear automatically if you have Excel installed).

• Click the ‘Browse’ button to select the path to the Excel file you want to import.

• Select the version of the Excel file (97-2003 is usually fine for files with a .XLS extension, or use 2007 for newer files with a .XLSX extension)

• Tick the ‘First Row has headers’ checkbox if your Excel file contains headers.

• Click Next.

  

1. On the ‘Choose a Destination‘ screen, select destination database:

• Select the ‘Server name’, Authentication (typically your sql username & password) and select a Database as destination. Click Next.

  

1. On the ‘Specify Table Copy or Query‘ window:

• For simplicity just select ‘Copy data from one or more tables or views’, click Next.

1. ‘Select Source Tables:‘ choose the worksheet(s) from your Excel file and specify a destination table for each worksheet. If you don’t have a table yet the wizard will very kindly create a new table that matches all the columns from your spreadsheet. Click Next.

   

2. Click Finish.

title	description	author	ms.author	ms.date	ms.service	ms.subservice	ms.topic	monikerRange
Import data from Excel to SQL Server or Azure SQL Database	This article describes methods to import data from Excel to SQL Server or Azure SQL Database. Some use a single step, others require an intermediate text file.	rwestMSFT	randolphwest	03/30/2023	sql	data-movement	conceptual	=azuresqldb-current||>=sql-server-2016||>=sql-server-linux-2017||=azuresqldb-mi-current

Import data from Excel to SQL Server or Azure SQL Database

[!INCLUDE SQL Server Azure SQL Database]

There are several ways to import data from Excel files to [!INCLUDE ssnoversion-md] or to Azure SQL Database. Some methods let you import data in a single step directly from Excel files; other methods require you to export your Excel data as text (CSV file) before you can import it.

This article summarizes the frequently used methods and provides links for more detailed information. A complete description of complex tools and services like SSIS or Azure Data Factory is beyond the scope of this article. To learn more about the solution that interests you, follow the provided links.

List of methods

There are several ways to import data from Excel. You may need to install SQL Server Management Studio (SSMS) to use some of these tools.

You can use the following tools to import data from Excel:

Export to text first ([!INCLUDE ssnoversion-md] and SQL Database)	Directly from Excel ([!INCLUDE ssnoversion-md] on-premises only)
Import Flat File Wizard	SQL Server Import and Export Wizard
BULK INSERT statement	SQL Server Integration Services (SSIS)
BCP	OPENROWSET function
Copy Wizard (Azure Data Factory)
Azure Data Factory

If you want to import multiple worksheets from an Excel workbook, you typically have to run any of these tools once for each sheet.

[!IMPORTANT]
To learn more, see limitations and known issues for loading data to or from Excel files.

Import and Export Wizard

Import data directly from Excel files by using the [!INCLUDE ssnoversion-md] Import and Export Wizard. You also can save the settings as a SQL Server Integration Services (SSIS) package that you can customize and reuse later.

1. In [!INCLUDEssManStudioFull], connect to an instance of the [!INCLUDEssNoVersion] [!INCLUDEssDE].

2. Expand Databases.

3. Right-click a database.

4. Select Tasks.

5. Choose to Import Data or Export Data:

   :::image type=»content» source=»../../integration-services/import-export-data/media/start-wizard-ssms.jpg» alt-text=»Start wizard SSMS»:::

This launches the wizard:

:::image type=»content» source=»media/excel-connection.png» alt-text=»Connect to an Excel data source»:::

To learn more, review:

• Start the SQL Server Import and Export Wizard
• Get started with this simple example of the Import and Export Wizard

Integration Services (SSIS)

If you’re familiar with SQL Server Integration Services (SSIS) and don’t want to run the [!INCLUDE ssnoversion-md] Import and Export Wizard, create an SSIS package that uses the Excel Source and the [!INCLUDE ssnoversion-md] Destination in the data flow.

To learn more, review:

• Excel Source
• SQL Server Destination

To start learning how to build SSIS packages, see the tutorial How to Create an ETL Package.

:::image type=»content» source=»media/excel-to-sql-data-flow.png» alt-text=»Components in the data flow»:::

OPENROWSET and linked servers

[!IMPORTANT]
In Azure SQL Database, you cannot import directly from Excel. You must first export the data to a text (CSV) file.

[!NOTE]
The ACE provider (formerly the Jet provider) that connects to Excel data sources is intended for interactive client-side use. If you use the ACE provider on [!INCLUDE ssnoversion-md], especially in automated processes or processes running in parallel, you may see unexpected results.

Distributed queries

Import data directly into [!INCLUDE ssnoversion-md] from Excel files by using the Transact-SQL OPENROWSET or OPENDATASOURCE function. This usage is called a distributed query.

[!IMPORTANT]
In Azure SQL Database, you cannot import directly from Excel. You must first export the data to a text (CSV) file.

Before you can run a distributed query, you have to enable the ad hoc distributed queries server configuration option, as shown in the following example. For more info, see ad hoc distributed queries Server Configuration Option.

sp_configure 'show advanced options', 1;
RECONFIGURE;
GO
sp_configure 'ad hoc distributed queries', 1;
RECONFIGURE;
GO

The following code sample uses OPENROWSET to import the data from the Excel Sheet1 worksheet into a new database table.

USE ImportFromExcel;
GO
SELECT * INTO Data_dq
FROM OPENROWSET('Microsoft.ACE.OLEDB.12.0',
    'Excel 12.0; Database=C:TempData.xlsx', [Sheet1$]);
GO

Here’s the same example with OPENDATASOURCE.

USE ImportFromExcel;
GO
SELECT * INTO Data_dq
FROM OPENDATASOURCE('Microsoft.ACE.OLEDB.12.0',
    'Data Source=C:TempData.xlsx;Extended Properties=Excel 12.0')...[Sheet1$];
GO

To append the imported data to an existing table instead of creating a new table, use the INSERT INTO ... SELECT ... FROM ... syntax instead of the SELECT ... INTO ... FROM ... syntax used in the preceding examples.

To query the Excel data without importing it, just use the standard SELECT ... FROM ... syntax.

For more info about distributed queries, see the following articles:

• Distributed Queries (Distributed queries are still supported in [!INCLUDE sssql19-md], but the documentation for this feature hasn’t been updated.)
• OPENROWSET
• OPENDATASOURCE

Linked servers

You can also configure a persistent connection from [!INCLUDE ssnoversion-md] to the Excel file as a linked server. The following example imports the data from the Data worksheet on the existing Excel linked server EXCELLINK into a new [!INCLUDE ssnoversion-md] database table named Data_ls.

USE ImportFromExcel;
GO
SELECT * INTO Data_ls FROM EXCELLINK...[Data$];
GO

You can create a linked server from SQL Server Management Studio (SSMS), or by running the system stored procedure sp_addlinkedserver, as shown in the following example.

DECLARE @RC INT;
DECLARE @server NVARCHAR(128);
DECLARE @srvproduct NVARCHAR(128);
DECLARE @provider NVARCHAR(128);
DECLARE @datasrc NVARCHAR(4000);
DECLARE @location NVARCHAR(4000);
DECLARE @provstr NVARCHAR(4000);
DECLARE @catalog NVARCHAR(128);

-- Set parameter values
SET @server = 'EXCELLINK';
SET @srvproduct = 'Excel';
SET @provider = 'Microsoft.ACE.OLEDB.12.0';
SET @datasrc = 'C:TempData.xlsx';
SET @provstr = 'Excel 12.0';

EXEC @RC = [master].[dbo].[sp_addlinkedserver] @server,
    @srvproduct,
    @provider,
    @datasrc,
    @location,
    @provstr,
    @catalog;

For more info about linked servers, see the following articles:

• Create Linked Servers
• OPENQUERY

For more examples and info about both linked servers and distributed queries, see the following article:

• How to use Excel with SQL Server linked servers and distributed queries

Prerequisite — Save Excel data as text

To use the rest of the methods described on this page — the BULK INSERT statement, the BCP tool, or Azure Data Factory — first you have to export your Excel data to a text file.

In Excel, select File | Save As and then select Text (Tab-delimited) (*.txt) or CSV (Comma-delimited) (*.csv) as the destination file type.

If you want to export multiple worksheets from the workbook, select each sheet, and then repeat this procedure. The Save as command exports only the active sheet.

[!TIP]
For best results with data importing tools, save sheets that contain only the column headers and the rows of data. If the saved data contains page titles, blank lines, notes, and so forth, you may see unexpected results later when you import the data.

The Import Flat File Wizard

Import data saved as text files by stepping through the pages of the Import Flat File Wizard.

As described previously in the Prerequisite section, you have to export your Excel data as text before you can use the Import Flat File Wizard to import it.

For more info about the Import Flat File Wizard, see Import Flat File to SQL Wizard.

BULK INSERT command

BULK INSERT is a Transact-SQL command that you can run from SQL Server Management Studio. The following example loads the data from the Data.csv comma-delimited file into an existing database table.

As described previously in the Prerequisite section, you have to export your Excel data as text before you can use BULK INSERT to import it. BULK INSERT can’t read Excel files directly. With the BULK INSERT command, you can import a CSV file that is stored locally or in Azure Blob storage.

USE ImportFromExcel;
GO
BULK INSERT Data_bi FROM 'C:Tempdata.csv'
   WITH (
      FIELDTERMINATOR = ',',
      ROWTERMINATOR = 'n'
);
GO

For more info and examples for [!INCLUDE ssnoversion-md] and SQL Database, see the following articles:

• Import Bulk Data by Using BULK INSERT or OPENROWSET(BULK…)
• BULK INSERT

BCP tool

BCP is a program that you run from the command prompt. The following example loads the data from the Data.csv comma-delimited file into the existing Data_bcp database table.

As described previously in the Prerequisite section, you have to export your Excel data as text before you can use BCP to import it. BCP can’t read Excel files directly. Use to import into [!INCLUDE ssnoversion-md] or SQL Database from a test (CSV) file saved to local storage.

[!IMPORTANT]
For a text (CSV) file stored in Azure Blob storage, use BULK INSERT or OPENROWSET. For an examples, see Example.

bcp.exe ImportFromExcel..Data_bcp in "C:Tempdata.csv" -T -c -t ,

For more info about BCP, see the following articles:

• Import and Export Bulk Data by Using the bcp Utility
• bcp Utility
• Prepare Data for Bulk Export or Import

Copy Wizard (ADF)

Import data saved as text files by stepping through the pages of the Azure Data Factory (ADF) Copy Wizard.

As described previously in the Prerequisite section, you have to export your Excel data as text before you can use Azure Data Factory to import it. Data Factory can’t read Excel files directly.

For more info about the Copy Wizard, see the following articles:

• Data Factory Copy Wizard
• Tutorial: Create a pipeline with Copy Activity using Data Factory Copy Wizard.

Azure Data Factory

If you’re familiar with Azure Data Factory and don’t want to run the Copy Wizard, create a pipeline with a Copy activity that copies from the text file to [!INCLUDE ssnoversion-md] or to Azure SQL Database.

As described previously in the Prerequisite section, you have to export your Excel data as text before you can use Azure Data Factory to import it. Data Factory can’t read Excel files directly.

For more info about using these Data Factory sources and sinks, see the following articles:

• File system
• SQL Server
• Azure SQL Database

To start learning how to copy data with Azure data factory, see the following articles:

• Move data by using Copy Activity
• Tutorial: Create a pipeline with Copy Activity using Azure portal

Common errors

Microsoft.ACE.OLEDB.12.0″ hasn’t been registered

This error occurs because the OLEDB provider isn’t installed. Install it from Microsoft Access Database Engine 2010 Redistributable. Be sure to install the 64-bit version if Windows and [!INCLUDE ssnoversion-md] are both 64-bit.

The full error is:

Msg 7403, Level 16, State 1, Line 3
The OLE DB provider "Microsoft.ACE.OLEDB.12.0" has not been registered.

Cannot create an instance of OLE DB provider «Microsoft.ACE.OLEDB.12.0» for linked server «(null)»

This indicates that the Microsoft OLEDB hasn’t been configured properly. Run the following Transact-SQL code to resolve this:

EXEC sp_MSset_oledb_prop N'Microsoft.ACE.OLEDB.12.0', N'AllowInProcess', 1;
EXEC sp_MSset_oledb_prop N'Microsoft.ACE.OLEDB.12.0', N'DynamicParameters', 1;

The full error is:

Msg 7302, Level 16, State 1, Line 3
Cannot create an instance of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)".

The 32-bit OLE DB provider «Microsoft.ACE.OLEDB.12.0» cannot be loaded in-process on a 64-bit SQL Server

This occurs when a 32-bit version of the OLD DB provider is installed with a 64-bit [!INCLUDE ssnoversion-md]. To resolve this issue, uninstall the 32-bit version and install the 64-bit version of the OLE DB provider instead.

The full error is:

Msg 7438, Level 16, State 1, Line 3
The 32-bit OLE DB provider "Microsoft.ACE.OLEDB.12.0" cannot be loaded in-process on a 64-bit SQL Server.

The OLE DB provider «Microsoft.ACE.OLEDB.12.0» for linked server «(null)» reported an error.

Cannot initialize the data source object of OLE DB provider «Microsoft.ACE.OLEDB.12.0» for linked server «(null)»

Both of these errors typically indicate a permissions issue between the [!INCLUDE ssnoversion-md] process and the file. Ensure that the account that is running the [!INCLUDE ssnoversion-md] service has full access permission to the file. We recommend against trying to import files from the desktop.

The full errors are:

Msg 7399, Level 16, State 1, Line 3
The OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" reported an error. The provider did not give any information about the error.

Msg 7303, Level 16, State 1, Line 3
Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)".

Next steps

• Get started with this simple example of the Import and Export Wizard
• Import data from Excel or export data to Excel with SQL Server Integration Services (SSIS)
• bcp Utility
• Move data by using Copy Activity

Introduction

We often have to perform data integration in SQL Server, with different data sources such as «.txt» files (tabular text or with separator character), «.csv» files or «.xls» (Excel) files.

It is always not possible to create a SSIS package to do this data import, a useful alternative is to use OPENROWSET method for importing data.

In this article, we will use data import from Excel files (.xls e .xlsx).

Building the Environment for Testing

So that we see the data import process steps from an Excel file to a table from database, we need:

• Create an Excel file to import sample;
• Configure Windows Server, installing the necessary components;
• Configure the necessary permissions to the SQL instance that we need to obtain data files.

Let’s prepare environment for data import!

Creating an Excel File to test

In this step, we will create an Excel file sample with just a few rows to demo.

Add a header row, to explicitly define the data: «ID», «Item Name» and «Date Created».

The data sequences is only to facilitate the visualization of the content that is being manipulated.

See this Excel file in the image below (click to enlarge)

Installing the necessary components in Windows Server

To get the data through a query inside SQL Server, use an OLE DB Data Provider.

Most files can now use the
Microsoft.ACE.OLEDB.12.0 Data Provider that can be obtained free through Data Connectivity Components.

This package will provide all ODBC and OLEDB drivers for data manipulation, as follow below:

File Type (extension)	Extended Properties
Excel 97-2003 Workbook (.xls)	Excel 8.0
Excel 2007-2010 Workbook (.xlsx)	Excel 12.0 XML
Excel 2007-2010 Macro-enabled workbook (.xlsm)	Excel 12.0 Macro
Excel 2007-2010 Non-XML binary workbook (.xlsb)	Excel 12.0

There are two versions of this package: «AccessDatabaseEngine.exe» for x86 platform and other «AccessDatabaseEngine_x64.exe» for x64 platform.

The minimum system requirements for this installation can be obtained in the same

download package page.

If you are installing the x86 package you must ensure that your user is allowed access to the Temporary directory of your Windows OS.

To know what your Temporary directory open the «Control Panel», click «Advanced System Settings» option. A window will open, select the «Advanced» tab and click the «Environment Variables» button.

A new window will open with your environment variables, including «TEMP» and «TMP» variables, indicating your Temporary directory.

See this windows in the image below (click to enlarge)

So if your operating system is Windows 32-bit (x86) is necessary to include read and write access to the user of your SQL Server instance.

It’s important to remember that the user of your SQL Server instance must be a local user or the default «Local System» account to grant this access.

See this window Service Properties in the image below

Enabling SQL Server Instance to Read File

The settings and permissions to execute a query external data has some details that should be performed to be able to get the data from an Excel files (.xls ou .xlsx) and also other formats.

The execution of distributed queries as OPENROWSET is only possible when the SQL Server instance has the
Ad Hoc Distributed Queries configuration enabled. By default, every SQL Server instance maintains this permission denied.

Note
The Advanced Settings should only be changed by an experienced professional or a certified professional in SQL Server. It’s important to note not use these commands in Production Databases without previous analysis. We recommend you run all tests in an isolated environment, at your own risk.

To enable this feature just use the sp_configure system stored procedure in your SQL instance to display its Advanced Settings in
show advanced options parameter and soon to follow, enable the Ad Hoc Distributed Queries setting to enabling the use of distributed queries.

---

USE [master]
GO

—CONFIGURING SQL INSTANCE TO ACCEPT ADVANCED OPTIONS
EXEC
sp_configure ‘show advanced options’, 1
RECONFIGURE
GO

—ENABLING USE OF DISTRIBUTED QUERIES
EXEC
sp_configure ‘Ad Hoc Distributed Queries’, 1
RECONFIGURE
GO

---

These changes in the Advanced settings only take effect after the execution of the RECONFIGURE command.

To get permission granted to use the Data Provider through sp_MSset_oledb_prop system stored procedure to link Microsoft.ACE.OLEDB.12.0 in
SQL Server using AllowInProcess parameter so we can use the resources of the Data Provider and also allow the use of dynamic parameters in queries through of
DynamicParameters  parameter for our queries can use T-SQL clauses.

---

USE [master]
GO

—ADD DRIVERS IN SQL INSTANCE
EXEC
master.dbo.sp_MSset_oledb_prop
N’Microsoft.ACE.OLEDB.12.0′,
N’AllowInProcess’, 1
GO

EXEC
master.dbo.sp_MSset_oledb_prop
N’Microsoft.ACE.OLEDB.12.0′,
N’DynamicParameters’, 1
GO

---

See
this output SQL script in the image below

After setting up your SQL instance to use the
Microsoft.ACE.OLEDB.12.0 Data Provider and make the appropriate access permissions, we can implement the distributed queries of other data sources,
in this case to Excel files. 

Querying and Importing the Spreadsheet

As this demo is for Excel files (.xls) we will perform a query using an OPENROWSET method with the Excel test file that was created earlier in this article. 

We use some parameters for this method to be able to data query:

• Data Provider — In this case, using Microsoft.ACE.OLEDB.12.0
• BULK Options      — File Version;Where it’s stored; Header (HDR); Import Mode (IMEX)
• Query                     —
  T-SQL statement with or without clauses to data filter and process.

---

—CONSULTING A SPREADSHEET
SELECT
* FROM
OPENROWSET(‘Microsoft.ACE.OLEDB.12.0’,
‘Excel 12.0; Database=C:MicrosoftTest.xls; HDR=YES; IMEX=1’,
‘SELECT * FROM [Plan1$]’) 
GO

---

See
this output SQL script in the image below

To data group and perform other tasks for data manipulation, the ideal is always load the data into the database. You can insert data into an existing table using the INSERT statement or you can create a table through of INTO command in SELECT statement.

---

—CONSULTING A SPREADSHEET
SELECT * 
INTO
TB_EXAMPLE
FROM OPENROWSET(‘Microsoft.ACE.OLEDB.12.0’,
‘Excel 12.0; Database=C:MicrosoftTest.xls; HDR=YES; IMEX=1’,
‘SELECT * FROM [Plan1$]’) 
GO

SELECT * FROM TB_EXAMPLE 
GO

---

See
this output SQL script in the image below

It’s also important to check if the SQL Server Service user has access in Windows directory where Excel files
are stored.

Conclusion

Have the possibility to use an alternative resource for importing data with T-SQL command is very useful, especially when we have to manipulate files in proprietary formats, as for .xlsx files where it’s necessary to use the Data Provider appropriate to obtain
the data correctly and with ease use.

It’s important to watch out that only users that have actually need to manipulate these files can use these resources, while minimizing the vulnerability of their environment through a permission in your SQL Server.

---

References

• OPENROWSET (Transact-SQL)
• Import Bulk Data by Using BULK INSERT or OPENROWSET(BULK…) (SQL Server)
• OLE DB Providers Tested with SQL Server
• Excel Source

---

See Also

• Transact-SQL Portal
• Wiki: Portal of TechNet Wiki Portals

---

Other Languages

• Importando uma planilha Excel para um Banco de Dados SQL Server (pt-BR)

---

 
This article was awarded the silver medal in the TechNet
Guru of April 2014

Microsoft Excel has been a traditional choice as a spreadsheet application for organizations across the world. The ease of access, power formulas, and the ability to make visually stunning reports has made Microsoft Excel is widely used tool. However, managing thousands of sheets can be a time-consuming and resource-intensive task that may also lead to some errors. A good solution is to import your Excel files to a scalable, reliable, and fast relational database management system like MySQL.

You can Import Excel into MySQL either by using simple SQL commands like LOAD DATA or opt for third-party tools. By importing your Excel files to MySQL, you can leverage the powerful MySQL engine to quickly query data and perform complex data manipulations.

In this article, you will learn how to effectively Import Excel into MySQL using 4 different methods.

What is Microsoft Excel?

Microsoft Excel is a spreadsheet application developed by Microsoft to organize and record data in a tabular format. Launched in 1985, Microsoft Excel is a widely used Spreadsheet software in businesses worldwide allowing you to organize and manipulate data through formulas in columns and rows. MS Excel is loaded with functionalities to perform several operations such as calculations, pivot tables, graph tools, etc.

Compatible with Microsoft Windows, macOS, Android, and iOS, MS Excel is included with the MS Office Suite. It is typically used by firms to record, organize and analyze financial data. MS Excel also offers VBA programming that can assist you in automating repetitive tasks.

Key Features of Microsoft Excel

• Conditional Formatting: MS Excel allows you to apply formats to a cell or range of cells, and have that formatting change depending on the value of the cell or the value of a formula.
• Built-in Formulae: MS Excel provides you with basic and advanced built-in formulae for sum, average, minimum, etc. You can use formula auditing to graph or trace the relationship between cells and formulas with blue arrows. You can track precedents (cells that provide data for a particular cell) or the cells that depend on the value of a particular cell. 
• Data Protection: Excel spreadsheets can be password protected on your laptop or PC. MS Excel also provides a robust system to recover data.
• Data Sorting & Filtering: You can easily perform the basic data sorting and filtering operation on your data in excel. MS Excel also provides Advanced filtering options for complex criteria.

What is MySQL?

MySQL is a popular Open-Source Relational Database Management System. MySQL data is stored in tables consisting of rows and columns. Introduced in 1995, MySQL is completely developed, distributed, and maintained by Oracle Corporation. Looking over the technical side, MySQL is written in the C and C ++ languages.

MySQL is compatible with multiple platforms such as Microsoft Windows, Oracle Solaris, AIX, Symbian, Linux, and macOS. You can use SQL commands to retrieve, change or add data from your MySQL tables. MySQL is also a vital component of the Modern LAMP stack, which consists of a Linux-based Operating System, Apache Web Server, MySQL Database, and PHP for processing.

SQL can also be used to define the table schema or even configure the relationship between the tables in the database. Client-Side Graphical User Interfaces such as MySQL WorkBench, SequelPro, or DBVisualizer can be used to type the SQL commands and the server will respond with the requested information. MySQL also offers a paid Enterprise version which includes premium support services and several extensions that can be installed as Server Plugins.

Key Features of MySQL

MySQL is widely used by organizations like Facebook, Flickr, Twitter, Wikipedia, and YouTube. This is due to the following set of MySQL’s eye-catching features: 

• Ease of Operation: With MySQL, you can work with a diverse set of programming languages ​​such as PHP, PERL, C, C ++, and JAVA. It also provides a set of intuitive tools to simplify time-consuming tasks such as Server Management, Reporting, and Data Analysis.
• Support for Several Data Structures: Allowing you to work with a broader range of datasets, MySQL offers full support for several Data structures like JSON and Geospatial data, as well as Logical, Numeric, Alphanumeric, Date, and Time data types.
• First-rate Performance: MySQL delivers best-in-class query performance across a variety of clustered servers. It provides a fast-loading utility with a separate memory cache and table index partitioning. MySQL can also efficiently handle fluctuating workloads and process large volumes of data at optimal speeds. This allows you to store more than 50 million rows of data in a table with a table’s default file size limit of 4 GB which can be increased to a theoretical limit of 8 million terabytes (TB).
• Open-Source: MySQL is under the GNU General Public License (GPL), which means it will always be freely available. It provides you the freedom to customize it on Oracle’s Open-Source MySQL codebase based on your needs.
• Localization: To make it user-friendly, MySQL supports multiple character sets, including latin1 (cp1252), german, big5, ujis, and more. You can also set the error message language that the server provides to the client.
• Data Security: MySQL provides full control over the Data Access Control settings. Robust mechanisms such as Access Privilege Systems and User Account Management allow you to regulate who can view or use your MySQL data. MySQL sets the highest standard with Host-based Verification and Password Encryption.

Why should you import Excel into MySQL?

Microsoft Excel is an easy-to-use spreadsheet application that allows you to directly access data and perform a combination of operations on this data. As you collect data and store it in your separate excel files, it becomes a huge task to track each sheet with millions of records in it. To simplify this, you can import Excel into MySQL. MySQL is a scalable, fast, and reliable database management system that allows you to store and query millions of rows of data using simple SQL commands.

Using MYSQL, you can also connect your Excel tables with one another tables using primary and foreign keys. MySQL can easily handle large datasets and allows you to manipulate data, filter data, update data and combine it. You can import Excel into MySQL and enjoy better speed, accuracy, & consistency for your ever-growing data needs.

• Method 1: Using Hevo Data to import Excel into MySQL
• Method 2: Using Sqlizer.io to Import Excel into MySQL
• Method 3: Using the Load Data Statement to Import Excel into MySQL
• Method 4: Import Excel into MySQL using phpMyAdmin

Method 1: Using Hevo Data to import Excel into MySQL

Hevo Data is a No-code Data Pipeline solution that can help you move data from 150+ data sources (including 40+ free sources like Google Drive & Google Sheets) to your desired destination such as MySQL, Data Warehouses, or BI tools in a completely hassle-free & automated manner. Using Hevo you can easily upload your Excel files present on your Google Drive to your MySQL Database.

Hevo also supports MySQL as a Source for loading data to a destination of your choice. Hevo is fully managed and completely automates the process of not only loading data from 150+ data sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

Hevo Data takes care of all your data preprocessing needs and lets you focus on key business activities and draw a more powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. 

Take a look at some of the salient features of Hevo:

• Blazing-fast Setup: Straightforward interface for new customers to work on, with minimal setup time.
• Reliability at Scale – With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 
• Monitoring and Observability – Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs 
• Stay in Total Control – When automation isn’t enough, Hevo offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    
• Transparent Pricing – Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in data flow. 
• Auto-Schema Management – Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps source schema with destination warehouse so that you don’t face the pain of schema errors.
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Without the need for converting your .xlsx file to .csv, you effortlessly import Excel into MySQL using Hevo by following the simple steps given below:

• Step 1: Upload your Excel files into your Google Drive.
• Step 2: Login to Hevo and naviagte to Pipleines > + Create. Select Google Drive as your Source and configure your Drive account by selecting the authentication method for connecting to Google Drive.

• Step 3: Finally, provide a name for your Pipeline and select all the folders whose Excel files you want to import to MySQL. Then, click on the Continue button.

• Step 4: For completing the process to import Excel into MySQL, you can start by providing your MySQL database credentials such as your authorized Username and Password, along with information about your Host IP Address and Port Number value. You will also need to provide a name for your database and a unique name for this destination.

Method 2: Using Sqlizer.io to Import Excel into MySQL

To import Excel into MySQL, you can use Sqlizer.io to convert your Excel files into SQL commands. You can achieve this by following the simple instructions given below: 

• Step 1: Click on the Browse button and select the Excel file you want to import to MySQL.
• Step 2: Select MySQL as your desired database. According to your excel file, check or uncheck My File has a Header Row.
• Step 3: Based on your Excel file, check Use CHECK IF TABLE EXISTS. For using the active worksheet, check the Use the active worksheet box.
• Step 4: You can also choose to enter the Worksheet name. For this example, the worksheet name Students is mentioned.
• Step 5: To import Excel into MySQL, you can either provide the data cell range or check the Convert the whole worksheet box to import the whole data.
• Step 6: Finally, name the table in which to import excel into MySQL. Then, click on the Convert My File button.

• Step 7: After your file is converted, you will get the following message. Now, download the queries or you can even copy the queries to execute them on MySQL.

After the queries have been executed, you can view your data in MySQL using the SELECT command.

Method 3: Using the Load Data Statement to Import Excel into MySQL

Using the LOAD DATA Statement, you can import Excel data into MySQL. To do that, follow the simple steps given below:

• Step 1: You have to first convert your .xlsx file to .csv file. For that, open up the excel file that you need to import.
• Step 2: Navigate to File > Save As. Select CSV (Comma delimited)(*.csv) as your file type and click on the Save button. 

• Step 3: Now, enter the LOAD DATA command shown below in your MySQL Workbench import Excel into MySQL.

# MySQL Version 8.0.27
LOAD DATA INFILE
'C:/ProgramFiles/MySQLExcel/import excel into mysql.csv'
INTO TABLE new_file
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY 'n'
IGNORE 1 ROWS;  

In the above process to import an excel file in MySQL workbench, the .csv file data will be added to the new_file table in your MySQL database without the first row as it contains the row headers. For this example, the .csv file uses a comma as the delimiter to separate 2 fields. You can also use FIELDS TERMINATED BY ‘t’ or FIELDS TERMINATED BY ‘ ‘ if your file’s fields are separated using a tab or a single space respectively. 

Alternatively, you can use the LOAD DATA command directly from the Command Line (CMD). 

Method 4: Import Excel into MySQL using phpMyAdmin

You can also import excel into MySQL using phpMyAdmin by first converting your .xlsx files to .csv files. For that, you have to first download and phpMyAdmin tool on your system. For this example, a new table named tb_students_phpmyadmin has been created in the MySQL Database. To import excel into MySQL, you can follow the simple steps given below: 

• Step 1: In phpMyAdmin, click on the Import tab and choose your desired .csv file. 
• Step 2: Now, enter the format-specific options and once you are done, click on the Go button present in the bottom right corner of your screen.

After clicking on the Go button, you will observe the data import confirmation messages for all your rows. 

• Step 3: Using the SELECT statement, you can check if the process to import excel into MySQL was successful or not.

Conclusion

In this article, you have learned how to effectively import Excel into MySQL using 4 different methods. Using Method 2, you convert your Excel file rows into SQL queries via sqlizer.io which you, later on, execute on your MySQL Workbench or Command-Line. Though this can be a time-consuming process if you are dealing with excel files containing thousands of rows. You can also use the LOAD DATA statement or a database administration tool like phpMyAdmin, though these require you to first convert the Excel files into CSV files. 

These 3 methods are a good option if you only need to rarely import Excel into MySQL with no requirement for processes like Data Cleaning & Data Standardisation. However, when you need to frequently import excel files with millions of rows of data in real-time that require complex data transformation, then you can opt for a No-Code Automated Data Integration platform like Hevo Data! 

Visit our Website to Explore Hevo

Hevo Data is a No-code Data Pipeline solution that can help you import data from a vast sea of sources like Google Drive to your desired destination such as MySQL, Data Warehouses, or BI tools. Using Hevo you can easily upload your Excel files present on your Google Drive to your MySQL Database. Hevo also supports MySQL as a Source for loading data to a destination of your choice. It is a reliable, completely automated, and secure service that doesn’t require you to write any code!  

If you are using MySQL as your Database Management System and searching for a no-fuss alternative to manual data integration, then Hevo can effortlessly automate this for you. Hevo, with its strong integration with 150+ sources (Including 40+ Free Sources like Google Drive & Google Sheets), allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.

Want to take Hevo for a ride? Sign Up for a 14-day free trial and simplify your Data Integration process. Do check out the pricing details to understand which plan fulfills all your business needs.

Tell us about your experience of completing the process to Import Excel into  MySQL! Share your thoughts with us in the comments section below.