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MariaDB vs Serverless: What are the differences?

Developers describe MariaDB as "An enhanced, drop-in replacement for MySQL". Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance. On the other hand, Serverless is detailed as "The most widely-adopted toolkit for building serverless applications". Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

MariaDB belongs to "Databases" category of the tech stack, while Serverless can be primarily classified under "Serverless / Task Processing".

"Drop-in mysql replacement" is the top reason why over 150 developers like MariaDB, while over 10 developers mention "API integration " as the leading cause for choosing Serverless.

MariaDB and Serverless are both open source tools. Serverless with 30.5K GitHub stars and 3.38K forks on GitHub appears to be more popular than MariaDB with 2.79K GitHub stars and 856 GitHub forks.

According to the StackShare community, MariaDB has a broader approval, being mentioned in 496 company stacks & 453 developers stacks; compared to Serverless, which is listed in 112 company stacks and 43 developer stacks.

What is MariaDB?

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

What is Serverless?

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
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      What are some alternatives to MariaDB and Serverless?
      PostgreSQL
      PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
      MySQL
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      Percona
      It delivers enterprise-class software, support, consulting and managed services for both MySQL and MongoDB across traditional and cloud-based platforms.
      Oracle
      Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      See all alternatives
      Decisions about MariaDB and Serverless
      StackShare Editors
      StackShare Editors
      MariaDB
      MariaDB
      MySQL
      MySQL

      Airbnb’s web experience is powered by a Rails monolith, called Monorail, that talks to several different Java services. MySQL databases store business data and are partitioned by functionality, with messages and calendar management, for example, stored separately from the main booking flow in their own databases.

      As traffic to the site continued growing, though, “one notable resource issue with MySQL databases [was] the increasing number of database connections from application servers.”

      Airbnb uses AWS’s Relational Database Service (RDS) to power their MySQL instances, and “RDS uses the community edition of MySQL server, which employs a one-thread-per-connection model of connection management.” With Airbnb’s scale, this meant that their databases would hit the C10K problem, which states that “there is an upper bound in the number of connections that MySQL server can accept and serve without dramatically increasing the number of threads running, which severely degrades MySQL server performance.”

      When an RDS MySQL server hits resource limits, users will have trouble connecting to the site.

      MySQL does have dynamic thread pooling, but it’s only available in the enterprise edition; AWS MySQL RDS, though, doesn’t offer this feature, meaning Airbnb didn’t have access to dynamic thread pooling out-of-the-box.

      After surveying several options, the team chose MariaDB MaxScale, which is “a MySQL database proxy that supports intelligent query routing in between client applications and a set of backend MySQL servers.”

      Instead of using the MariaDB MaxScale off-the-shelf, however, they decided to fork it and implement their own version that would include connection pooling. Other MaxScale features, like request throttling and query blocklisting were implemented as well.

      To enable horizontal scaling of the web application, the team deployed a MaxScale database proxy service in between app servers and MySQL servers. Through the service discovery system SmartStack, applications now “discover and connect to the database proxy service instead of the MySQL database,” allowing horizontal scaling to meet capacity demands.

      Additionally, new Airbnb MaxScale proxy server instances can be launched to further enable horizontal scaling.

      See more
      Nitzan Shapira
      Nitzan Shapira
      at Epsagon · | 11 upvotes · 105.6K views
      atEpsagonEpsagon
      AWS Lambda
      AWS Lambda
      GitHub
      GitHub
      Java
      Java
      Go
      Go
      Node.js
      Node.js
      npm
      npm
      Serverless
      Serverless
      Python
      Python

      At Epsagon, we use hundreds of AWS Lambda functions, most of them are written in Python, and the Serverless Framework to pack and deploy them. One of the issues we've encountered is the difficulty to package external libraries into the Lambda environment using the Serverless Framework. This limitation is probably by design since the external code your Lambda needs can be usually included with a package manager.

      In order to overcome this issue, we've developed a tool, which we also published as open-source (see link below), which automatically packs these libraries using a simple npm package and a YAML configuration file. Support for Node.js, Go, and Java will be available soon.

      The GitHub respoitory: https://github.com/epsagon/serverless-package-external

      See more
      Michal Nowak
      Michal Nowak
      Co-founder at Evojam · | 7 upvotes · 61.9K views
      atEvojamEvojam
      Azure Functions
      Azure Functions
      Firebase
      Firebase
      AWS Lambda
      AWS Lambda
      Serverless
      Serverless

      In a couple of recent projects we had an opportunity to try out the new Serverless approach to building web applications. It wasn't necessarily a question if we should use any particular vendor but rather "if" we can consider serverless a viable option for building apps. Obviously our goal was also to get a feel for this technology and gain some hands-on experience.

      We did consider AWS Lambda, Firebase from Google as well as Azure Functions. Eventually we went with AWS Lambdas.

      PROS
      • No servers to manage (obviously!)
      • Limited fixed costs – you pay only for used time
      • Automated scaling and balancing
      • Automatic failover (or, at this level of abstraction, no failover problem at all)
      • Security easier to provide and audit
      • Low overhead at the start (with the certain level of knowledge)
      • Short time to market
      • Easy handover - deployment coupled with code
      • Perfect choice for lean startups with fast-paced iterations
      • Augmentation for the classic cloud, server(full) approach
      CONS
      • Not much know-how and best practices available about structuring the code and projects on the market
      • Not suitable for complex business logic due to the risk of producing highly coupled code
      • Cost difficult to estimate (helpful tools: serverlesscalc.com)
      • Difficulty in migration to other platforms (Vendor lock⚠️)
      • Little engineers with experience in serverless on the job market
      • Steep learning curve for engineers without any cloud experience

      More details are on our blog: https://evojam.com/blog/2018/12/5/should-you-go-serverless-meet-the-benefits-and-flaws-of-new-wave-of-cloud-solutions I hope it helps 🙌 & I'm curious of your experiences.

      See more
      Amazon ElastiCache
      Amazon ElastiCache
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      Memcached
      Memcached
      Redis
      Redis
      Python
      Python
      AWS Lambda
      AWS Lambda
      Amazon RDS
      Amazon RDS
      Microsoft SQL Server
      Microsoft SQL Server
      MariaDB
      MariaDB
      Amazon RDS for PostgreSQL
      Amazon RDS for PostgreSQL
      Rails
      Rails
      Ruby
      Ruby
      Heroku
      Heroku
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk

      We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

      We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

      In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

      Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

      See more
      Julien DeFrance
      Julien DeFrance
      Principal Software Engineer at Tophatter · | 2 upvotes · 14K views
      atSmartZipSmartZip
      Amazon SageMaker
      Amazon SageMaker
      Amazon Machine Learning
      Amazon Machine Learning
      AWS Lambda
      AWS Lambda
      Serverless
      Serverless
      #FaaS
      #GCP
      #PaaS

      Which #IaaS / #PaaS to chose? Not all #Cloud providers are created equal. As you start to use one or the other, you'll build around very specific services that don't have their equivalent elsewhere.

      Back in 2014/2015, this decision I made for SmartZip was a no-brainer and #AWS won. AWS has been a leader, and over the years demonstrated their capacity to innovate, and reducing toil. Like no other.

      Year after year, this kept on being confirmed, as they rolled out new (managed) services, got into Serverless with AWS Lambda / FaaS And allowed domains such as #AI / #MachineLearning to be put into the hands of every developers thanks to Amazon Machine Learning or Amazon SageMaker for instance.

      Should you compare with #GCP for instance, it's not quite there yet. Building around these managed services, #AWS allowed me to get my developers on a whole new level. Where they know what's under the hood. Where they know they have these services available and can build around them. Where they care and are responsible for operations and security and deployment of what they've worked on.

      See more
      Joshua Dean Küpper
      Joshua Dean Küpper
      CEO at Scrayos UG (haftungsbeschränkt) · | 5 upvotes · 36.1K views
      atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
      Sentry
      Sentry
      GitLab
      GitLab
      PostgreSQL
      PostgreSQL
      MariaDB
      MariaDB

      We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and @Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQLs extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

      See more
      Aviad Mor
      Aviad Mor
      CTO & Co-Founder at Lumigo · | 5 upvotes · 10.1K views
      atLumigoLumigo
      Serverless
      Serverless
      CircleCI
      CircleCI
      AWS Lambda
      AWS Lambda

      Our backend is serverless based, with many AWS Lambda , with CI/CD, using CircleCI and Serverless. This allows to develop with awesome agility and move fast. Since we update our lambdas daily, we needed a way to make sure we did not run into AWS's max limit of versions per lambda. We use the open source in link below to clear them out and stay clear of the limit.

      See more
      Aliadoc Team
      Aliadoc Team
      at aliadoc.com · | 5 upvotes · 85.1K views
      atAliadocAliadoc
      Bitbucket
      Bitbucket
      Visual Studio Code
      Visual Studio Code
      Serverless
      Serverless
      Google Cloud Storage
      Google Cloud Storage
      Google App Engine
      Google App Engine
      Cloud Functions for Firebase
      Cloud Functions for Firebase
      Firebase
      Firebase
      CloudFlare
      CloudFlare
      Create React App
      Create React App
      React
      React
      #Aliadoc

      In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.

      For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.

      For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.

      We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.

      Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.

      See more
      Tim Nolet
      Tim Nolet
      Founder, Engineer & Dishwasher at Checkly · | 5 upvotes · 20.1K views
      atChecklyHQChecklyHQ
      Node.js
      Node.js
      Google Cloud Functions
      Google Cloud Functions
      Azure Functions
      Azure Functions
      Amazon CloudWatch
      Amazon CloudWatch
      Serverless
      Serverless
      AWS Lambda
      AWS Lambda

      AWS Lambda Serverless Amazon CloudWatch Azure Functions Google Cloud Functions Node.js

      In the last year or so, I moved all Checkly monitoring workloads to AWS Lambda. Here are some stats:

      • We run three core functions in all AWS regions. They handle API checks, browser checks and setup / teardown scripts. Check our docs to find out what that means.
      • All functions are hooked up to SNS topics but can also be triggered directly through AWS SDK calls.
      • The busiest function is a plumbing function that forwards data to our database. It is invoked anywhere between 7000 and 10.000 times per hour with an average duration of about 179 ms.
      • We run separate dev and test versions of each function in each region.

      Moving all this to AWS Lambda took some work and considerations. The blog post linked below goes into the following topics:

      • Why Lambda is an almost perfect match for SaaS. Especially when you're small.
      • Why I don't use a "big" framework around it.
      • Why distributed background jobs triggered by queues are Lambda's raison d'être.
      • Why monitoring & logging is still an issue.

      https://blog.checklyhq.com/how-i-made-aws-lambda-work-for-my-saas/

      See more
      Praveen Mooli
      Praveen Mooli
      Technical Leader at Taylor and Francis · | 11 upvotes · 157.6K views
      MongoDB Atlas
      MongoDB Atlas
      Amazon S3
      Amazon S3
      Amazon DynamoDB
      Amazon DynamoDB
      Amazon RDS
      Amazon RDS
      Serverless
      Serverless
      Docker
      Docker
      Terraform
      Terraform
      Travis CI
      Travis CI
      GitHub
      GitHub
      RxJS
      RxJS
      Angular 2
      Angular 2
      AWS Lambda
      AWS Lambda
      Amazon SQS
      Amazon SQS
      Amazon SNS
      Amazon SNS
      Amazon Kinesis Firehose
      Amazon Kinesis Firehose
      Amazon Kinesis
      Amazon Kinesis
      Flask
      Flask
      Python
      Python
      ExpressJS
      ExpressJS
      Node.js
      Node.js
      Spring Boot
      Spring Boot
      Java
      Java
      #Data
      #Devops
      #Webapps
      #Eventsourcingframework
      #Microservices
      #Backend

      We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

      To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

      To build #Webapps we decided to use Angular 2 with RxJS

      #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

      See more
      Interest over time
      Reviews of MariaDB and Serverless
      Review ofMariaDBMariaDB

      MySQL was founded by Allan Larsson, Michael Widenius and David Axmark in the year 1995, 19 years ago. It was released under the name of co-founder Michael Widenius daughter, ‘My‘. This project was released under GNU General Public License as well as under certain Proprietary License. MySQL was owned by MySQL AB firm until it went into the hands of Oracle Corporation. It is written in Programming Language – C and C++ and is available for Windows, Linux, Solaris, MacOS and FreeBSD.

      In the year 2009, Michael Widenius started working on MarisDB as a fork of MySQL. In the year 2012 the bricks of nonprofit MariaDB Foundation was laid. It was named after the founder’s daughter Maria.

      MariaDB is a fork of MySQL Relational Database Management System which again is released under GNU General Public License. It is written in Programming Language – C, C++, Perl and Bash and is available for Systems Linux, Windows, Solaris, MacOS and FreeBSD.

      How developers use MariaDB and Serverless
      Avatar of Scrayos UG (haftungsbeschränkt)
      Scrayos UG (haftungsbeschränkt) uses MariaDBMariaDB

      Aside from Redis, we use MariaDB to store long-term information like user-data and big-data like regeneration-information for our open-world servers. We extensively use the relational aspects of MariaDB in joins, nested queries and unions.

      Avatar of Seungkwon Park
      Seungkwon Park uses MariaDBMariaDB

      mysql보다 mariaDB가 join면에서 우수하다는 문서를 읽었습니다. 이 부분은 저의 블로그에서도 다뤘고 저의 word press 블로그는 mysql 대신 mariaDB 를 사용합니다.

      특히 limit 기능이 pagenation 처리를 할 때 너무 직관적이고 편해서 mariaDB, mysql을 사랑합니다.

      Avatar of Ana Phi Sancho
      Ana Phi Sancho uses MariaDBMariaDB

      Introduced in computer science course.managing relational database management systems, database analytics, and for data processing

      Avatar of nrise
      nrise uses MariaDBMariaDB

      수 백만개가 넘는 태그 키워드의 자동완성을 위해서 별도의 데이터베이스를 구축하였습니다. MariaDB 는 MySQL 을 포크한 프로젝트입니다. MySQL 과의 강력한 호환성을 지니며, 큰 튜닝 없이 강력한 성능을 보장합니다.

      Avatar of Dolls Kill
      Dolls Kill uses MariaDBMariaDB

      MariaDB has allowed us to easily scale out our DB cluster. Also has better replication tools than MySQL

      Avatar of betterPT
      betterPT uses ServerlessServerless

      We use AWS Lambda / Serverless as a Facade for out integrations with EMRs.

      Avatar of JimmyCode
      JimmyCode uses ServerlessServerless

      Oh yeah! We run on lambdas.

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