Entries in database (18)

Tuesday
Sep012020

MySQL on Azure Performance Benchmark – ScaleGrid vs. Azure Database

Microsoft Azure is one of the most popular cloud providers in the world, and a natural fit for database hosting on applications leveraging Microsoft across their infrastructure. MySQL is the number one open source database that’s commonly hosted through Azure instances. While Microsoft offers their own Azure Database product, there are other alternatives available that may be able to help you improve your MySQL performance. In this blog post, we compare Azure Database for MySQL vs. ScaleGrid MySQL on Azure so you can see which provider offers the best throughput and latency performance. We measure latency in ms 95th percentile latency.

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Monday
May112020

Reducing Your Database Hosting Costs: DigitalOcean vs. AWS vs. Azure

Reducing Your Database Hosting Costs: DigitalOcean vs. AWS vs. Azure

If you’re hosting your databases in the cloud, choosing the right cloud service provider is a significant decision to make for your long-term hosting costs. This is especially apparent in today's world where organizations are doing whatever they can to optimize and reduce their costs. Over the last few weeks, we have been inundated with requests from SMB customers looking to improve the ROI on their database hosting. In this article, we are going to compare three of the most popular cloud providers, AWS vs. Azure vs. DigitalOcean for their database hosting costs for MongoDB® database to help you decide which cloud is best for your business.

Comparing Cloud Instance Costs

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Monday
Feb172020

Important Health Checks for your MySQL Master-Slave Servers

In a MySQL master-slave high availability (HA) setup, it is important to continuously monitor the health of the master and slave servers so you can detect potential issues and take corrective actions. In this blog post, we explain some basic health checks you can do on your MySQL master and slave nodes to ensure your setup is healthy. The monitoring program or script must alert the high availability framework in case any of the health checks fails, enabling the high availability framework to take corrective actions in order to ensure service availability.

MySQL Master Server Health Checks

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Wednesday
Jan222020

Follower Clusters – 3 Major Use Cases for Syncing SQL & NoSQL Deployments

Follower Clusters – 3 Major Use Cases for Syncing SQL & NoSQL Deployments

Follower clusters are a ScaleGrid feature that allows you to keep two independent database systems (of the same type) in sync. Unlike cloning or replication, this allows you to maintain an active, point-in-time copy of your production data. This extra cluster, known as a follower cluster, can be leveraged for multiple use cases, including for analyzing, optimizing and testing your application performance for MongoDB, MySQL and PostgreSQL. In this blog post, we will cover the top three scenarios to leverage follower clusters for your application.

How Do Follower Clusters Differ From Replication?

Unlike a static clone, this data imports on a set schedule so your follower cluster is always in sync with your production cluster. Here are a few critical ways in which it differs from replication:

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Wednesday
Jan082020

PostgreSQL Connection Pooling: Part 2 – PgBouncer

PostgreSQL Connection Pooling: Part 2 – PgBouncer

When it comes to connection pooling in the PostgreSQL world, PgBouncer is probably the most popular option. It’s a very simple utility that does exactly one thing – it sits between the database and the clients and speaks the PostgreSQL protocol, emulating a PostgreSQL server. A client connects to PgBouncer with the exact same syntax it would use when connecting directly to PostgreSQL – PgBouncer is essentially invisible.

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Tuesday
Oct292019

How to Improve MySQL AWS Performance 2X Over Amazon RDS at The Same Cost

How to Improve MySQL AWS Performance 2X Over Amazon RDS at The Same Cost

AWS is the #1 cloud provider for open-source database hosting, and the go-to cloud for MySQL deployments. As organizations continue to migrate to the cloud, it’s important to get in front of performance issues, such as high latency, low throughput, and replication lag with higher distances between your users and cloud infrastructure. While many AWS users default to their managed database solution, Amazon RDS, there are alternatives available that can improve your MySQL performance on AWS through advanced customization options and unlimited EC2 instance type support. ScaleGrid offers a compelling alternative to hosting MySQL on AWS that offers better performance, more control, and no cloud vendor lock-in and the same price as Amazon RDS. In this post, we compare the performance of MySQL Amazon RDS vs. MySQL Hosting at ScaleGrid on AWS High Performance instances.

TLDR

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Friday
Oct182019

PostgreSQL Connection Pooling: Part 1 – Pros & Cons

PostgreSQL Connection Pooling: Part 1 – Pros & Cons

A long time ago, in a galaxy far far away, ‘threads’ were a programming novelty rarely used and seldom trusted. In that environment, the first PostgreSQL developers decided forking a process for each connection to the database is the safest choice. It would be a shame if your database crashed, after all.

Since then, a lot of water has flown under that bridge, but the PostgreSQL community has stuck by their original decision. It is difficult to fault their argument – as it’s absolutely true that:

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Monday
Sep162019

Managing High Availability in PostgreSQL – Part III: Patroni

Managing High Availability in PostgreSQL – Part III: Patroni - ScaleGrid Blog

In our previous blog posts, we discussed the capabilities and functioning of PostgreSQL Automatic Failover (PAF) by Cluster Labs and Replication Manager (repmgr) by 2ndQuadrant. In the final post of this series, we will review the last solution, Patroni by Zalando, and compare all three at the end so you can determine which high availability framework is best for your PostgreSQL hosting deployment.

Patroni for PostgreSQL

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Tuesday
Sep032019

Top Redis Use Cases by Core Data Structure Types

Top Redis Use Cases by Core Data Structure Types - ScaleGrid Blog

Redis, short for Remote Dictionary Server, is a BSD-licensed, open-source in-memory key-value data structure store written in C language by Salvatore Sanfillipo and was first released on May 10, 2009. Depending on how it is configured, Redis can act like a database, a cache or a message broker. It’s important to note that Redis is a NoSQL database system. This implies that unlike SQL (Structured Query Language) driven database systems like MySQL, PostgreSQL, and Oracle, Redis does not store data in well-defined database schemas which constitute tables, rows, and columns. Instead, Redis stores data in data structures which makes it very flexible to use. In this blog, we outline the top Redis use cases by the different core data structure types.

Data Structures in Redis

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Thursday
Jun272019

2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence

2019 Open Source Database Report: Top Databases, Public Cloud vs. On-Premise, Polyglot Persistence

Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Or, considering adding a new database to your application and want to see which combinations are most popular? We found all the answers you need at the Percona Live event last month, and broke down the insights into the following free trends reports:

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