MySQL Schema Design: Back to The Future?

Once developers find themselves in the MySQL world, they will almost certainly hear some advice on how they should go about designing database schemas in MySQL. This blog post will provide insight into what you should consider when dealing with database schemas in MySQL.

Preface

Designing a MySQL database schema is an inevitable part of the career of every MySQL database administrator or even a developer. Developers and MySQL database administrators usually turn to the schema design side of MySQL to improve query performance, normalize their databases, add or drop certain indexes, modify columns, also for other things.

Generally, what one database administrator considers to be a “good” database design might not seem so perfect for another DBA. Everyone has their own set of preferences — depending on experience and other things — but in general, even while MySQL does move forward at a rapid pace, with improvements being made left and right, MySQL schema design practices do not change much.

We are going to start from some of the basic things that you personally may already know but might not be as readily apparent to other developers.

The Basics of MySQL Schema Design

Some of the general advice regarding MySQL schema design sounds something like this:

1. Make sure MySQL databases only store data that is needed.
2. Choose optimal data types for certain use cases.
3. If we store variable character values in columns, we use VARCHAR. If we store text, we should use TINYTEXT, TEXT, MEDIUMTEXT , or LONGTEXT. If we find ourselves using integers, we should probably look into TINYINT, SMALLINT, MEDIUMINT, INT, or BIGINT depending on a specific use case.
4. We should give our data types a specific length — for example, we should avoid using VARCHAR(255) when VARCHAR(100) would suffice, etc. By doing so, we enable MySQL to reduce data size.
5. If we have a lot of data, we should use indexes to improve performance, but we must also keep in mind that we should avoid using redundant and (or) duplicate indexes.

The general consensus among DBAs is that MySQL schema design should be based around a few core points:

1. Define the requirements for the database.
2. Gather, organize and refine the data. If needed, add indexes to improve performance.
3. Create relationships among tables.
4. Refine and normalize the database design.

#schema #mysql #database

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Best MySQL DigitalOcean Performance – ScaleGrid vs. DigitalOcean Managed Databases

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MySQL is the all-time number one open source database in the world, and a staple in RDBMS space. DigitalOcean is quickly building its reputation as the developers cloud by providing an affordable, flexible and easy to use cloud platform for developers to work with. MySQL on DigitalOcean is a natural fit, but what’s the best way to deploy your cloud database? In this post, we are going to compare the top two providers, DigitalOcean Managed Databases for MySQL vs. ScaleGrid MySQL hosting on DigitalOcean.

At a glance – TLDR
ScaleGrid Blog - At a glance overview - 1st pointCompare Throughput
ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads. Read now

ScaleGrid Blog - At a glance overview - 2nd pointCompare Latency
On average, ScaleGrid achieves almost 30% lower latency over DigitalOcean for the same deployment configurations. Read now

ScaleGrid Blog - At a glance overview - 3rd pointCompare Pricing
ScaleGrid provides 30% more storage on average vs. DigitalOcean for MySQL at the same affordable price. Read now

MySQL DigitalOcean Performance Benchmark
In this benchmark, we compare equivalent plan sizes between ScaleGrid MySQL on DigitalOcean and DigitalOcean Managed Databases for MySQL. We are going to use a common, popular plan size using the below configurations for this performance benchmark:

Comparison Overview
ScaleGridDigitalOceanInstance TypeMedium: 4 vCPUsMedium: 4 vCPUsMySQL Version8.0.208.0.20RAM8GB8GBSSD140GB115GBDeployment TypeStandaloneStandaloneRegionSF03SF03SupportIncludedBusiness-level support included with account sizes over $500/monthMonthly Price$120$120

As you can see above, ScaleGrid and DigitalOcean offer the same plan configurations across this plan size, apart from SSD where ScaleGrid provides over 20% more storage for the same price.

To ensure the most accurate results in our performance tests, we run the benchmark four times for each comparison to find the average performance across throughput and latency over read-intensive workloads, balanced workloads, and write-intensive workloads.

Throughput
In this benchmark, we measure MySQL throughput in terms of queries per second (QPS) to measure our query efficiency. To quickly summarize the results, we display read-intensive, write-intensive and balanced workload averages below for 150 threads for ScaleGrid vs. DigitalOcean MySQL:

ScaleGrid MySQL vs DigitalOcean Managed Databases - Throughput Performance Graph

For the common 150 thread comparison, ScaleGrid averages almost 40% higher throughput over DigitalOcean for MySQL, with up to 46% higher throughput in write-intensive workloads.

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SCHEMAS in SQL Server -MS SQL Server – Zero to Hero Query Master

Introduction

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,

• MS SQL Server – Zero to Hero Query Master – Part 1
• MS SQL Server – Zero to Hero Query Master – Part 2

A glimpse of previous articles

Part 1

In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.

Part 2

• We learned to create a database and maintain it using SQL statements.
• Best practice methods were also mentioned.

#sql server #benefits of schemas #create schema in sql #database schemas #how to create schema in sql server #schemas #schemas in sql server #sql server schemas #what is schema in sql server

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Why use our Landscapes for your landscape design?

• Superior experience
• Friendly personal service
• Choice of design layout
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If you are a gardener or have a gardening company please do not hesitate to contact us for a quote.
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MySQL Schema Design: Back to The Future?

This blog post will cover strategies employed by database administrators to design MySQL database schemas with performance in mind.

Preface

Designing a MySQL database schema is an inevitable part of the career of every MySQL database administrator or even a developer. Developers and MySQL database administrators usually turn to the schema design side of MySQL to improve query performance, normalize their databases, add or drop certain indexes, modify columns, also for other things.

Generally, what one database administrator considers to be a “good” database design might not seem so perfect for another DBA. Everyone has their own set of preferences—depending on experience and other things—but in general, even while MySQL does move forward at a rapid pace, with improvements being made left and right, MySQL schema design practices do not change much.

We are going to start from some of the basic things that you personally may already know but might not be as readily apparent to other developers.

The Basics of MySQL Schema Design

Some of the general advice regarding MySQL schema design sounds something like this:

1. Make sure MySQL databases only store data that is needed.
2. Choose optimal data types for certain use cases.
3. If we store variable character values in columns, we use VARCHAR. If we store text, we should use TINYTEXT, TEXT, MEDIUMTEXT , or LONGTEXT. If we find ourselves using integers, we should probably look into TINYINT, SMALLINT, MEDIUMINT, INT, or BIGINT depending on a specific use case.
4. We should give our data types a specific length—for example, we should avoid using VARCHAR(255) when VARCHAR(100) would suffice, etc. By doing so, we enable MySQL to reduce data size.
5. If we have a lot of data, we should use indexes to improve performance, but we must also keep in mind that we should avoid using redundant and (or) duplicate indexes.

The general consensus among DBAs is that MySQL schema design should be based around a few core points:

1. Define the requirements for the database.
2. Gather, organize and refine the data. If needed, add indexes to improve performance.
3. Create relationships among tables.
4. Refine and normalize the database design.

#mysql #schema

MySQL Schema Design: Back to The Future?

Once developers find themselves in the MySQL world, they will almost certainly hear some advice on how they should go about designing database schemas in MySQL. This blog post will provide insight into what you should consider when dealing with database schemas in MySQL.

Preface

Designing a MySQL database schema is an inevitable part of the career of every MySQL database administrator or even a developer. Developers and MySQL database administrators usually turn to the schema design side of MySQL to improve query performance, normalize their databases, add or drop certain indexes, modify columns, also for other things.

Generally, what one database administrator considers to be a “good” database design might not seem so perfect for another DBA. Everyone has their own set of preferences — depending on experience and other things — but in general, even while MySQL does move forward at a rapid pace, with improvements being made left and right, MySQL schema design practices do not change much.

We are going to start from some of the basic things that you personally may already know but might not be as readily apparent to other developers.

The Basics of MySQL Schema Design

Some of the general advice regarding MySQL schema design sounds something like this:

1. Make sure MySQL databases only store data that is needed.
2. Choose optimal data types for certain use cases.
3. If we store variable character values in columns, we use VARCHAR. If we store text, we should use TINYTEXT, TEXT, MEDIUMTEXT , or LONGTEXT. If we find ourselves using integers, we should probably look into TINYINT, SMALLINT, MEDIUMINT, INT, or BIGINT depending on a specific use case.
4. We should give our data types a specific length — for example, we should avoid using VARCHAR(255) when VARCHAR(100) would suffice, etc. By doing so, we enable MySQL to reduce data size.
5. If we have a lot of data, we should use indexes to improve performance, but we must also keep in mind that we should avoid using redundant and (or) duplicate indexes.

The general consensus among DBAs is that MySQL schema design should be based around a few core points:

1. Define the requirements for the database.
2. Gather, organize and refine the data. If needed, add indexes to improve performance.
3. Create relationships among tables.
4. Refine and normalize the database design.

#schema #mysql #database