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Introduction to MySQL Relational Database

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Relation Control System of MySQL relational database

From the specific definition of the relational database, people think it’s too critical for maintaining and will create confusion. But that is not a true statement; a relational database’s main agenda is to avoid any kind of confusion or complication between multiple tables involved with that specific database, where it helps a developer to maintain and verify easily without any struggle.

ISupposewe consider any relational design, that is very common, maintains a strict relationship between all the related tables defined in the database. Suppose we have an Inventory Controlling System. In that case, we must maintain strict relationships between all tables involved, providing detailed descriptions related to the inventory.

Also, it needs to maintain a more strict relationship with those child tables, which additionally impacts any kind of data manipulation activity like inserting or deleting from that specific inventory. As examples, we will consider three tables involved in the inventory controlling system, assuming three are interrelated.

Table Name: Inventory

ID (Primary Key) Description Price Stock

Table Name: Sales_Staff

ID (Primary Key) Name Email contact

Table Name: Invoice

ID (Primary Key) SalesStaff_ID( Foreign Key of Sales_Staff Primary Key) Inventory_ID (Foreign Key of Inventory Primary Key) Quantity Price comment

Now considering the above three tables, we can plan the relationship between multiple tables using primary key and foreign key constraints. In the above example, invoice is the main transactional table, where all the transactional data has been stored successfully for every invoice generation on individual customers or end-user. It stores all the invoice data successfully for any kind of reference.

Now invoice should generate from some inventory details where a quantity of the entire inquiry has been stored for one entire shop or organization. Now considering two key master tables Inve,ntory and Sales_Staff, both the tables maintain the main store details of any specific item in that shop or organization, whereas Sales_Staff maintains all the staff details which are working in that shop or organization. Rather than mkeepingthe same staff or specific item every time in inventory transactional details, it holds oa particularreference of those master tables, which some administrator of the shop or organization maintains.

So by this specific approach, we can easily avoid data redundancy or repetition, which always helps fetch data based on a maintained relationship between multiple tables. This example gives one key characteristic of any relational database like MySQL relational database that is assuming one invoice data always holds the reference of specific inventory and sales staff, but inventory or sales staff is never able to change or update anything in the created invoice.

So here, it maintained one too many relationships where one inventory data can exist in invoice multiple times, and the same sales staff data can exist in invoice numerous times. This relationship helps the developer for fetching data smoothly with specific joining conditions and also understanding or designing any ER diagram will be very easy for them. Here is a key point to mention: when a salesperson tries to sell something from the stock, they must maintain this kind of relationship to ensure a successful sale.

Whenever any inventory is added to the invoice,, it automatically subtracts stock from the original inventory, so it will always provide a proper validation message whenever a a salesperson tries to create any kind of invoice for a a specific inventory. If we look closely on those table relationship, then inventory have one primary key name Id, and Sales_Staff have one primary key name ,ID, but invoice has two foreign key, which is maintained the relationship with Inventory and Sales_Staff tables.

Guidance of installing My SQL Relational Database

1. Download the MySQL relational database from bthe elow link:

2. Executing bthe elow script for unpacking the archival package:

tar –xzf xxxx-db.tar.gz


chúng tôi

chúng tôi

4. Now run MySQL basic command:

Mysql –p (password)

5. Now, just follow the instructions mention in chúng tôi and sakila-schema.sql.

6. If you follow all instructions correctly, you will create a new database named ‘sakila’ and it will automatically display in the list of MySQL relational databases.

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Complete Guide To Mysql Date_Sub()

Definition on MySQL DATE_SUB()

The date_sub() is a built-in function of MySQL database server, which is used to make the difference of a time or date value from a date or DateTime value and outputs the result as date or DateTime. The function accepts two arguments; the first argument passed is starting date or initial date from which the second argument, which is the time interval, is subtracted argument to generate the output. The function can output the result in various units. The unit should be passed in the function we want our output to be.

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Below is the syntax of MySQL Date_sub():

DATE_SUB (start_date,time expression unit)

Mathematically, the Date_sub function can also be written as below:

Date_sub=difference(start_date,time interval)

The above syntax of date_sub() takes two arguments. They are:

start_date is the initial date or datetime value or beginning date.

A time expression is a string representing a time value subtracting from the start_date value. The unit is the time unit as year, month, day, etc.

The unit can be microseconds, seconds, minutes, hours, weeks, months, years, quarters, second_microsecond, minute_microsecond, minute_second, hour_microsecond, hour_second, hour_minute, day_microsecond, day_second, day_minute, day_hour, year_month, etc.

The following statement uses the date_sub () function to subtract two days from May 24, 2023:

Examples of MySQL DATE_SUB()

Below are the examples mentioned for better understanding :

Example #1


Select date_sub('2024-05-24',interval 2 day) AS result;


The above example’s start date is 2023-05-24, written in the yyyy-mm-dd format. The second argument is a 2-day interval. The output of the date_sub() function is 2023-05-22 in the console.

Example #2

Below is the query where the time interval is of 5 hours:


Select date_sub('2024-05-24',interval 5 hour) AS result;


Since the time interval is 5 hours, the function’s output is a DateTime value.

Query with a Negative Interval

The interval or second argument’s time expression could be positive or negative. We can handle both positive and negative time intervals passed as the second parameter in the date_sub() function. When the time interval is negative, the date_sub() function functions similarly to the date_add() function, as demonstrated in the query below:

Example #3


Select date_sub('2024-05-24',interval -2 day) AS result;


In the above query, we have passed a negative 2-day interval as our second parameter. Therefore, two days are added to the starting or initial days in the output.

Example #4


Select date_sub('2024-02-29',interval -2 day) AS result;


In the above query, the start date is 2023-02-29, and the second argument, i.e., the interval is a negative interval of 2 days. Technically, the output of the query must be 2023-02-30, which is an invalid date as there is no 30th day in February month. Therefore the output of the query is March 2nd, 2023.

Query for an Invalid or Abnormal Date Example #5


Select date_sub('2024-02-35',interval -2 Day) AS result;0


In the example below, 2023-02-35 is an invalid date; therefore, it gives the output NULL and a warning message in the output console.

Example #6 Show warnings;


Example #7


Select date_sub(null,interval 1 Day) AS result;


Since, In the above query, we have passed a null value in the initial date value as our first parameter, whatever we give as an interval in the second argument will output a null value.

Query for Automatic Adjusted Day

When subtracting a MONTH, YEAR, or YEAR_MONTH interval from a date, if the result is a date with a day number greater than the maximum day of the new month, the day will be adjusted to the maximum day in the new month.

The below query explains the automatically adjusted day concept easily.

Example #8


Select date_sub('2024-05-30',interval 1 month) as result;


In this example, we subtracted one month from May 24th, 2023, so the outcome is April 30th, April.

Example #9


Select Date_sub('2024-05-24',interval 2 week) AS 'negative week'; Select Date_sub('2024-05-24', interval 2 month) AS 'negative month'; Select Date_sub('2024-05-24',interval 2 quarter) AS 'negative quarter';


Example #10


Select date_sub('2024-05-24 11:00:00', interval 6 hour) As result;

Example #11


Select date_sub(curdate(), interval 6 hour) AS result


Example #12


select date_sub(curdate(), interval -2 day) result;


Example #13


Select date_sub('2024-05-24 12:20:20.000010',interval 1000 microsecond) As result;


Example #14


Select date_sub('2024-05-24 12:20:20.000010',interval 750 microsecond)As result;



If we specify a time interval value that is too small for the specified unit, the DATE_SUB() will assume that the user did not provide the left-most part of the interval value.

DATE_SUB function with a negative value as a parameter is the same as that of the DATE_ADD function.

The DATE_SUB function is used in the below-mentioned versions of MySQL:

MySQL 5.7,  MySQL 5.6,  MySQL 5.5,  MySQL 5.1,  MySQL 5.0,  MySQL 4.1,  MySQL 4.0,  MySQL 3.23

Conclusion – MySQL DATE_SUB()

In this article, we learned how MySQL date_sub() function subtracts the time from a date or datetime value in various units. We have tried to explain every aspect of the date_sub() function easily with the query with almost all the units like microseconds, days, months, years, weeks, quarters, etc., along with the screenshots of the output console for a better understanding of the reader. We have also learned about the negative date-time concepts of the date_sub() function.

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Mysql Select Statement With Examples

What is SELECT query in MySQL?

SELECT QUERY is used to fetch the data from the MySQL database. Databases store data for later retrieval. The purpose of MySQL Select is to return from the database tables, one or more rows that match a given criteria. Select query can be used in scripting language like PHP, Ruby, or you can execute it via the command prompt.

SQL SELECT statement syntax

It is the most frequently used SQL command and has the following general syntax


SELECT is the SQL keyword that lets the database know that you want to retrieve data.

FROM tableName is mandatory and must contain at least one table, multiple tables must be separated using commas or joined using the JOIN keyword.

WHERE condition is optional, it can be used to specify criteria in the result set returned from the query.

GROUP BY is used to put together records that have the same field values.

HAVING condition is used to specify criteria when working using the GROUP BY keyword.

ORDER BY is used to specify the sort order of the result set.


The Star symbol is used to select all the columns in table. An example of a simple SELECT statement looks like the one shown below.

SELECT * FROM `members`;

The above statement selects all the fields from the members table. The semi-colon is a statement terminate. It’s not mandatory but is considered a good practice to end your statements like that.

Practical examples

You can learn to import the .sql file into MySQL WorkBench

The Examples are performed on the following two tables

Table 1: members table

membership_ number full_names gender date_of_ birth physical_ address postal_ address contct_ number email

1 Janet Jones Female 21-07-1980 First Street Plot No 4 Private Bag 0759 253 542 [email protected]

2 Janet Smith Jones Female 23-06-1980 Melrose 123 NULL NULL

3 Robert Phil Male 12-07-1989 3rd Street 34 NULL 12345

4 Gloria Williams Female 14-02-1984 2nd Street 23 NULL NULL NULL

Table 2: movies table

movie_id title director year_released category_id

1 Pirates of the Caribean 4 Rob Marshall 2011 1

2 Forgetting Sarah Marshal Nicholas Stoller 2008 2

3 X-Men NULL 2008 NULL

4 Code Name Black Edgar Jimz 2010 NULL

5 Daddy’s Little Girls NULL 2007 8

6 Angels and Demons NULL 2007 6

7 Davinci Code NULL 2007 6

9 Honey mooners John Schultz 2005 8

16 67% Guilty NULL 2012 NULL

Getting members listing

Let’s suppose that we want to get a list of all the registered library members from our database, we would use the script shown below to do that.

SELECT * FROM `members`;

Executing the above script in MySQL workbench produces the following results.

membership_ number full_names gender date_of_ birth physical_ address postal_ address contct_ number email

1 Janet Jones Female 21-07-1980 First Street Plot No 4 Private Bag 0759 253 542 [email protected]

2 Janet Smith Jones Female 23-06-1980 Melrose 123 NULL NULL

3 Robert Phil Male 12-07-1989 3rd Street 34 NULL 12345

4 Gloria Williams Female 14-02-1984 2nd Street 23 NULL NULL NULL

Our above query has returned all the rows and columns from the members table.

Let’s say we are only interested in getting only the full_names, gender, physical_address and email fields only. The following script would help us to achieve this.

SELECT `full_names`,`gender`,`physical_address`, `email` FROM `members`;

Executing the above script in MySQL workbench produces the following results.

full_names gender physical_address email

Janet Jones Female First Street Plot No 4 [email protected]

Janet Smith Jones Female Melrose 123

Robert Phil Male 3rd Street 34

Gloria Williams Female 2nd Street 23 NULL

Getting movies listing

Remember in our above discussion that we mention expressions been used in SELECT statements. Let’s say we want to get a list of movie from our database. We want to have the movie title and the name of the movie director in one field. The name of the movie director should be in brackets. We also want to get the year that the movie was released. The following script helps us do that.

SELECT Concat(`title`, ' (', `director`, ')') , `year_released` FROM `movies`;


The Concat () MySQL function is used join the columns values together.

The line “Concat (`title`, ‘ (‘, `director`, ‘)’) gets the title, adds an opening bracket followed by the name of the director then adds the closing bracket.

String portions are separated using commas in the Concat () function.

Executing the above script in MySQL workbench produces the following result set.

Concat(`title`, ‘ (‘, `director`, ‘)’) year_released

Pirates of the Caribean 4 ( Rob Marshall) 2011

Forgetting Sarah Marshal (Nicholas Stoller) 2008

NULL 2008

Code Name Black (Edgar Jimz) 2010

NULL 2007

NULL 2007

NULL 2007

Honey mooners (John Schultz) 2005

NULL 2012

Alias field names

The above example returned the Concatenation code as the field name for our results. Suppose we want to use a more descriptive field name in our result set. We would use the column alias name to achieve that. The following is the basic syntax for the column alias name


“[AS]” is the optional keyword before the alias name that denotes the expression, value or field name will be returned as.

“`alias_name`” is the alias name that we want to return in our result set as the field name.

The above query with a more meaningful column name

SELECT Concat(`title`, ' (', `director`, ')') AS 'Concat', `year_released` FROM `movies`;

We get the following result

Concat year_released

Pirates of the Caribean 4 ( Rob Marshall) 2011

Forgetting Sarah Marshal (Nicholas Stoller) 2008

NULL 2008

Code Name Black (Edgar Jimz) 2010

NULL 2007

NULL 2007

NULL 2007

Honey mooners (John Schultz) 2005

NULL 2012

Getting members listing showing the year of birth

Suppose we want to get a list of all the members showing the membership number, full names and year of birth, we can use the LEFT string function to extract the year of birth from the date of birth field. The script shown below helps us to do that.

SELECT `membership_number`,`full_names`,LEFT(`date_of_birth`,4) AS `year_of_birth` FROM members;


“LEFT(`date_of_birth`,4)” the LEFT string function accepts the date of birth as the parameter and only returns 4 characters from the left.

“AS `year_of_birth`” is the column alias name that will be returned in our results. Note the AS keyword is optional, you can leave it out and the query will still work.

Executing the above query in MySQL workbench against the myflixdb gives us the results shown below.

membership_number full_names year_of_birth

1 Janet Jones 1980

2 Janet Smith Jones 1980

3 Robert Phil 1989

4 Gloria Williams 1984

SQL using MySQL Workbench

We are now going to use MySQL workbench to generate the script that will display all the field names from our categories table.

2. MySQL workbench will automatically create a SQL query and paste in the editor.

3. Query Results will be show

Notice that we didn’t write the SELECT statement ourselves. MySQL workbench generated it for us.

Why use the SELECT SQL command when we have MySQL Workbench?

Now, you might be thinking why learn the SQL SELECT command to query data from the database when you can simply use a tool such as MySQL workbench’s to get the same results without knowledge of the SQL language. Of course that is possible, but learning how to use the SELECT command gives you more flexibility and control over your SQL SELECT statements.

MySQL workbench falls in the category of “Query by Example” QBE tools. It’s intended to help generate SQL statements faster to increase the user productivity.

Learning the SQL SELECT command can enable you to create complex queries that cannot be easily generated using Query by Example utilities such as MySQL workbench.

To improve productivity you can generate the code using MySQL workbench then customize it to meet your requirements. This can only happen if you understand how the SQL statements work!


The SQL SELECT keyword is used to query data from the database and it’s the most commonly used command.

The simplest form has the syntax “SELECT * FROM tableName;”

Expressions can also be used in the select statement . Example “SELECT quantity + price FROM Sales”

The SQL SELECT command can also have other optional parameters such as WHERE, GROUP BY, HAVING, ORDER BY. They will be discussed later.

MySQL workbench can help develop SQL statements, execute them and produce the output result in the same window.

How To Use The Tableau Union Database?

Introduction to Tableau Union

Tableau union is used to append the two or more tables by different options. Here the tables to be combined should be present in the same data connection linked to the same data source. If the data source manages union, the other new union option is viewed in the left pane of the data source once it is connected to the data.

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What is a Tableau Union?

In simple, a tableau union is used to join multiple tables that are present under the same data source and connection. Supported connectors have various functions between tableau online, tableau server, and tableau desktop. If the data source works on the union option, it is present in the left end pane on the data source site once the data connection is established. To achieve the preeminent result, the tables to be combined under the union option should have a similar structure. Every table should have the same count of fields and an associated field that has the matching data type and field names.

How to Use the Tableau Union Database?

The tables are unioned using the wildcard search option in the tableau database or desktop.

To implement this method, use a character in the wildcard, that is, asterisk * that fits the pattern or sequence of the array in the worksheet names, excel workbook, text files, .pdf files, JSON files, google sheets, and database tables.

Select the wildcard automatic option in the union dialog box.

Include: Select the search option if the user prefers to find the tables that should be included in the union. For example, the user can give * 2023 in the Include option in the excel sheet, ending with 2023 in the names. The search option gives the output as all the months present under 2023 from the selected or linked connection. Then choose to apply to get results.

Include and Expand a search to subfolders: If the user enters *2024 in the include option and selects the expand a search to subfolders in the check box, it looks at all the excel sheets under the name of 2023 in the current folder, and it extends its search in the worksheets that ends with 2024 in the additional worksheet present in the subfolder also.

Include and Expand Search to the Parent Folder: If the user enters *2024 in the include option and chooses to expand a search to the parent folder, it displays the name with 2023 in the current folder, then gives the additional sheets in the subfolder, then looks all the parallel workbook and displays all the files with 2023.

Include and Expand a Search to the Subfolders along with Expanding a Search to the Parent Folder: If the user enters *2024 in the include option and chooses both the expand a search to the subfolders along with expanding a search to the parent folder, it looks for all the worksheets in the current folder, then it goes for the related fields in the subfolder, then it extends the search in all the parallel folder and gives the result.

Tableau Union Editing

Tableau has three important functions under union that enable the user to perform rename a union, modify or customize a union and remove a union.

1. Rename a Union

Give a suitable name for the union table.

Day Customer Purchases Type

1 Ram 7 Credit

2 Sam 8 Credit

3 Kam 9 Credit

Day Customer Purchases


4 Hari 4 Credit

5 Sri 3 Credit

6 Dini 2 Credit

Day Customer Purchases

1 Ram 7 Credit

2 Sam 8 Credit

3 Kam 9 Credit

4 Hari 4 Credit

5 Sri 3 Credit

6 Dini 2 Credit

2. Modify a Union

The user can customize a union by removing or adding tables by using the below steps.

Choose the edit union option from the drop-down arrow in the union.

If the user wants to remove the table, he can hover on it and remove it accordingly. If he wants to add a new table, he can drag a table from the data source page.

Choose ok once all modifications are done.

3. Remove a Union

Merge a mismatched name in union:

When the table column is not matched in the union, it adds zero values in the resultant table.

Choose the columns which need to be merged.

In the column drop-down option, choose merge mismatched fields.

Example of Tableau Union

Below are the simple functions by tableau union that works under the database.

Join option can be used in the table that is unioned.

Two unioned tables can be combined again with the join option.

Union generates mandatory fields like table name and sheet, which can be used with the join key.

If the name range is present in the union, zero values are viewed in the sheet field.

The field option that emerged from merge can be changed and used as a pivot, split, or join key.

In tableau desktop, when the user has to work in Excel, he can use wildcard search to include the name ranges, but it gets excluded from the tables when data is interpreted.

To combine the JSON file using union, it should have .log extension or .txt, or .json format.

When the user implies wildcard search to combine files in .pdf, the output is placed in the initial .pdf file.


Hence, the user can use the tableau union option and combine all his files in the same database source. When the user works on the database, he can customize the union to a structured query.

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This is a guide to Tableau Union. Here we discuss the introduction, and how to use the tableau union database? editing an example. You may also have a look at the following articles to learn more –

How To Select A Cloud Database For Organizations?

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Google Cloud Platform (GCP) consists of many database services. GCP offers three reference architectures for global data distribution – a hybrid, multi-cloud, and regional distribution. It would help to consider these architectures when choosing a Google database service.

In this post, we’ll explain data distribution in GCP and provide an overview of Google’s popular cloud database services, including critical considerations when evaluating and choosing a service. We’ll also show how NetApp Cloud Volumes ONTAP can help centralize and simplify the management of Google’s cloud database resources.

This is part of our series of comprehensive guides to cloud storage technologies.

Deploying databases on Google Cloud

Google Cloud Platform (GCP) supports three primary deployment models: single cloud, hybrid, and multi-cloud.

Single cloud deployment

The simplest deployment model is to deploy databases only on Google Cloud via:

• Creation of new cloud databases on Google

Hybrid deployment: Google Cloud and on-premises resources

A hybrid deployment is practical when you have applications in the cloud that need access to on-premises databases or vice versa. For example, if you do on-premise marketing analytics and need to access customer databases hosted in the cloud.

There are three primary considerations for deploying a database in a hybrid model—with some data in Google Cloud and some on-premises:

• Main database – you need to decide if your central database will be stored locally or in the cloud. If you choose the cloud, GCP resources can act as a data center for on-premises resources. Your internal resources can sync data to the cloud for remote use or backup if you choose local. This allows you to maintain mirrored databases to provide failover during a crash.

• Portability – The type of data storage you choose affects the portability of your data. To ensure reliable data transfer and consistent configuration and management, you must consider cross-platform storage such as MySQL. Using homogeneous databases on-premise and in the cloud provides that you don’t have to reformat or change the data schema, allowing you to transfer it as needed quickly.

The following diagram shows an example of a hybrid architecture with Google Cloud and on-premise systems.

Image source

Multicloud Deployment: Including Google Cloud and other providers

When considering a multi-cloud deployment, you should be aware of the following:

• Integration – it is essential to ensure that client systems can seamlessly access databases regardless of the cloud in which they are deployed. You can use open-source client libraries to ensure seamless database availability across clouds such as clouds (see the JDBC guide).

• Database Migration – With multiple cloud providers, you may need to migrate data between clouds. It would help if you used database replication tools or export/import processes to migrate databases to GCP. There are several Google Cloud migration tools that you can use to migrate data to Google Cloud, such as Google Storage Transfer.

The following diagram shows a multi-cloud deployment involving GCP and another public cloud provider.

Image source

Google Cloud Database Services

GCP offers several Google Cloud database services to choose from. Below is an introduction to each.

Cloud SQL

Cloud SQL is a fully managed Google Cloud relational database service compatible with SQL Server, MySQL, and PostgreSQL. It includes automatic backup, data replication, and disaster recovery features to ensure high availability and resilience. You can integrate this service with Kubernetes, App Engine and BigQuery

Every day Cloud SQL use cases include:

• Lift and move local SQL databases to the cloud

• Extensive SQL data analysis

• Content Management System (CMS) data storage and scalability support.

• Database management using Infrastructure as Code (IaC)

• Development and deployment of container applications and microservices

Cloud Spanner

Cloud Spanner is another fully managed relational database service from Google Cloud. It differs from Cloud SQL in that it focuses on allowing you to combine the benefits of a relational structure with non-relational scalability.

Examples of using Cloud Spanner include:

• Supply chain management and manufacturing

• Financial trading, analysis, and prediction

• Logistics and transport


BigQuery is a fully managed serverless data warehouse. You can use it to perform data analysis through SQL and query data streams. This service includes a built-in data transfer service to help you migrate data from on-premises sources, including Teradata.

BigQuery includes features for machine learning, business intelligence, and geospatial analytics. These features are provided through BI Engine, BigQuery ML, and GIS.

Usage examples for BigQuery include:

• Process analytics and optimization

• Big data processing and analysis

• Behavioral analytics and predictions based on machine learning

• Modernization of the data warehouse

Cloud Bigtable

Cloud Bigtable is a fully managed NoSQL database service from Google Cloud. It is designed for large operational and analytical tasks. Cloud Bigtable features high zero-downtime configuration, availability,  and sub-10ms latency. You can integrate it with various tools, including BigQuery,  TensorFlow, and Apache Services.

Examples of using Cloud Bigtable include:

• Financial analysis and forecasting

• Internet of Things (IoT) data reception and processing

Cloud Firestore

Cloud Firestore is a fully managed serverless Google Cloud NoSQL database designed for serverless application development. You can use it to store, synchronize and query data for web, mobile, and IoT applications. It includes features for offline support, live sync, and built-in security. You can integrate Firestore with Firebase, GCP’s mobile development platform, to make building and managing apps easier.

Examples of uses for Cloud Firestore include:

• Mobile and web applications with online and offline options

• Multi-user, collaborative applications

• Real-time analysis

• Social media applications

• Gaming forums and leaderboards

Firebase database in real time

Realtime Database is a Google Cloud NoSQL database that is part of the Firebase platform. It allows you to store and sync data in real-time and includes caching features for offline use. The real-time database also will enable you to implement declarative authentication, matching users by identity or pattern. It includes mobile and web software development kits (SDKs) for easier and faster application development.

Usage examples for Firebase Realtime Database include:

• Developing applications that work across devices

• Third-party payment processing

• Machine learning integration

Cloud memory storage

Cloud Memory store is a fully managed Google Cloud in-memory data store. It is designed to be scalable, highly available, and secure. Cloud Memory store enables application caches with sub-millisecond latency to access data.

Examples of using Cloud Memory store include:

• Lift and shift application migration

• Application of machine learning

• Real-time analysis

• Low latency data caching and loading

Pick a Google Cloud database.

Even after exploring the database options in Google Cloud, deciding which choices suit you can be challenging. This allows you to optimise your implementations according to the capabilities of the database rather than trying to tailor the database service to fit all needs.

Cloud SQL

Cloud SQL is a good choice when you need relational database functionality but don’t need more than 10TB of storage or more than 4000 concurrent connections. You must also be skilled in on-premise management.

Cloud Spanner

Cloud Spanner is a good choice when you plan to use a large amount of data (more than 10TB) and need transactional consistency. It is also good to use sharding for higher throughput and availability.

If you know or think you may need to be able to scale your Google Cloud database horizontally, Cloud Scanner is a better choice than Cloud SQL. If you are starting with Cloud SQL and need to migrate to Cloud Spanner eventually, be prepared to rewrite the application in addition to migrating the database.

Cloud Firestore/Datastore

Cloud Firestore or Datastore are good options when you plan to focus on application development and need live sync and offline support.

Cloud Datastore is recommended if you need to store unstructured data in JSON documents. This is compared to when you need to store structured data, in which Cloud Spanner is recommended.

Another factor to consider is whether you need Atomicity, Consistency, Isolation, and Durability (ACID). You must choose Cloud Spanner because Cloud Datastore only offers atomic and persistent transactions.

Cloud Bigtable

Cloud Bigtable is a good choice if you use a large amount of data with a single key. In simple words, it works well for low-latency and high throughput.

If you need to analyze one area, Cloud Bigtable is preferred over Cloud Spanner. However, Cloud Spanner is the recommended solution if you need multi-region traffic. For example, Cloud Bigtable is a good choice for a time series application built for DevOps monitoring. Meanwhile, Cloud Spanner is the recommended choice for an infrastructure monitoring platform designed for a software-as-a-service (SaaS) offering.

Cloud memory storage

Cloud Memorystore is a good choice if you use key-value datasets and transaction latency is your primary concern.

If you don’t need disk persistence and only use a caching service, Cloud Memorystore should be your choice. However, if you are concerned about issues such as cache and database consistency or stream processing, you should choose Cloud Bigtable. Likewise, whenever your data volume is too large to fit in memory, Cloud Memorystore is not the best choice for you.

Google Cloud Database Management with ONTAP Cloud Volumes

NetApp Cloud Volumes ONTAP, the leading enterprise-grade storage management solution, provides secure and proven storage management services on AWS, Azure, and Google Cloud. Cloud Volumes ONTAP supports capacities up to 368 TB and supports various use cases such as file services, databases, DevOps, or any other enterprise workload with a robust feature set including high availability, data protection, storage efficiency, Kubernetes integration, and more.


Google Cloud offers a variety of storage options for you to choose from. These services form the base of many other cloud services, and understanding your options can help you manage your cloud more efficiently.

Google Cloud Platform (GCP) supports three primary deployment models: single cloud, hybrid, and multi-cloud. Portability, Managed Services, and central database

GCP offers several Google Cloud database services to choose from. Below is an introduction to each:- Cloud SQL, Cloud Spanner, BigQuery, and Cloud Bigtable

Multicloud deployments allow you to combine databases deployed in Google Cloud with database services from other cloud providers. When considering a multi-cloud deployment, you should know the following: Integrity & Database Migration.

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How To Recover A Deleted Database In Windows

How to recover a deleted database in Windows






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In case you’re trying to recover a deleted database, either because it happened by mistake, or you think it could have been moved, there are solutions to fix it.

Most of the time, your computer has a backup copy of the deleted database, so recovery involves:

Restoring the database from the backup database, or

Restoring the deleted database to a previous state.

We’ll show you how to do both so as to recover a deleted database.

How to restore deleted databases Solution 1: Restore a deleted database from the backup database

In order to restore a deleted database, your computer has to have a backup copy of the file or folder, which is also known as ‘known good copy’ of the database file or folder.

This copy is one which you are sure of its integrity and design.

To set off the restoration process, use the Backup Database command within Microsoft Office Access so as to make backups. However, you can also use any known good copy to restore the deleted database such as that stored in a USB flash drive.

There are two ways to restore a deleted database in this case:

Restore the entire deleted database

Selectively restore, or restore part of the deleted database

Without a backup copy, data loss, corrupted database design and unwanted changes are expected so you need to make backups regularly.

How to restore an entire database

Restoring an entire database simply means you’re taking the backup of the database, and replacing the previously deleted database that may have been damaged, or has other issues altogether.

Missing database files almost always have backup copies so replacing the database means you locate the backup copy, and then put it where the deleted database should be – the correct location – because some databases or programs are linked to objects in the particular database, and if not restored correctly, these will not work, or you may have to recreate them all over again.

Before restoring an entire database, delete the damaged file, and replace it with the backup copy.

ALSO READ: 5 best local data backup software to use

Expert tip:

If you intend to restore a part of the deleted database, import the object from the backup copy into the database with the object you want to restore.

Follow these steps to restore files from a backup:

Firstly, ensure the media or drive your backup copy is saved on is available

Select Control Panel

Follow the instructions in the wizard

Solution 2: Restore a deleted database to previous state/version

A previous version of a database has copies of files and folders saved automatically by Windows as part of a restoration point, or restore point.

Such copies are also known as shadow copies.

In order to restore files and folders to previous versions or previous state, do the following:

Select File Explorer

Go to the folder that contained the deleted database

How to restore a deleted database to a previous state

Follow the steps below to do this:

Select File Explorer

Go to the folder that contained the deleted database


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