Google Cloud Functions might be a bit more popular than MariaDB. We know about 43 links to it since March 2021 and only 34 links to MariaDB. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The first reason is that serverless architectures are inherently scalable and elastic. They automatically scale up or down based on the incoming workload without requiring manual intervention through serverless compute services like AWS Lambda, Azure Functions, or Google Cloud Functions. - Source: dev.to / 25 days ago
The FaaS platform gained a lot of popularity which resulted in many competitors. There was OSS providers like OpenFaaS or Fission. There were of course the commercial versions to like Azure Functions and Google Cloud Functions. - Source: dev.to / about 1 month ago
One of the issues developers can encounter when developing in Cloud Functions is the time taken to deploy changes. You can help reduce this time by dynamically loading some of your Python classes. This allows you to make iterative changes to just the area of your application that you’re working on. - Source: dev.to / 7 months ago
I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights. Source: 8 months ago
Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment. - Source: dev.to / 11 months ago
In a landscape filled with open-source and commercial relational databases, this article focuses on the four most prominent open-source databases - PostgreSQL, MySQL, MariaDB, and SQLite. These DBMS are the most preferred databases per the SO’s 2023 survey. - Source: dev.to / 7 days ago
WARNING: The host '(...)' could not be looked up with /usr/local/bin/resolveip. This probably means that your libc libraries are not 100 % compatible With this binary MariaDB version. The MariaDB daemon, mysqld, should work Normally with the exception that host name resolving will not work. This means that you should use IP addresses instead of hostnames When specifying MariaDB privileges ! Installing... - Source: dev.to / 10 months ago
i'm running MariaDB 10.6 from mariadb.org Repos in Debian 11. For authentication I'm using PAM and Active Directory. Source: 12 months ago
1-db-1 | The latest information about MariaDB is available at https://mariadb.org/. Source: about 1 year ago
Cat /etc/redhat-release Rocky Linux release 9.1 (Blue Onyx) Yum info mariadb-server Last metadata expiration check: 1:42:14 ago on Sun 09 Apr 2023 03:56:00 PM IST. Installed Packages Name : mariadb-server Epoch : 3 Version : 10.5.16 Release : 2.el9_0 Architecture : x86_64 Size : 62 M Source : mariadb-10.5.16-2.el9_0.src.rpm Repository : @System From repo :... Source: about 1 year ago
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
Salesforce Platform - Salesforce Platform is a comprehensive PaaS solution that paves the way for the developers to test, build, and mitigate the issues in the cloud application before the final deployment.
MySQL - The world's most popular open source database
AWS Lambda - Automatic, event-driven compute service
Microsoft SQL - Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.