Alternatives to Badger  logo

Alternatives to Badger

Badger, Mongoose, MySQL, PostgreSQL, and MongoDB are the most popular alternatives and competitors to Badger .
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What is Badger and what are its top alternatives?

Badger is written out of frustration with existing KV stores which are either natively written in Go and slow, or fast but require usage of Cgo. Badger aims to provide an equal or better speed compared to industry leading KV stores (like RocksDB), while maintaining the entire code base in Go natively.
Badger is a tool in the Databases category of a tech stack.
Badger is an open source tool with 10.2K GitHub stars and 888 GitHub forks. Here’s a link to Badger 's open source repository on GitHub

Top Alternatives to Badger

  • Badger

    Badger

    Domain management you'll enjoy. Domains effectively drive the entire internet, shouldn't they be easier to manage? We thought so, and thus, Badger was born! You shouldn't have to auction off your house and sacrifice your first born to transfer domains, you should be able to press a button that says "Transfer Domain" and be done with it. That is our philosophy, and we think you will appreciate it. Stop letting domain registrars badger you, and start using... Badger! ...

  • Mongoose

    Mongoose

    Let's face it, writing MongoDB validation, casting and business logic boilerplate is a drag. That's why we wrote Mongoose. Mongoose provides a straight-forward, schema-based solution to modeling your application data and includes built-in type casting, validation, query building, business logic hooks and more, out of the box. ...

  • MySQL

    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. ...

  • PostgreSQL

    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. ...

  • MongoDB

    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. ...

  • Microsoft SQL Server

    Microsoft SQL Server

    Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions. ...

  • SQLite

    SQLite

    SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file. ...

  • MariaDB

    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. ...

Badger alternatives & related posts

Badger logo

Badger

10
26
0
A new way of registering and managing your domains.
10
26
+ 1
0
PROS OF BADGER
    Be the first to leave a pro
    CONS OF BADGER
      Be the first to leave a con

      related Badger posts

      Mongoose logo

      Mongoose

      1.5K
      1.2K
      54
      MongoDB object modeling designed to work in an asynchronous environment
      1.5K
      1.2K
      + 1
      54
      PROS OF MONGOOSE
      • 17
        Well documented
      • 15
        Several bad ideas mixed together
      • 10
        JSON
      • 8
        Actually terrible documentation
      • 2
        Recommended and used by Valve. See steamworks docs
      • 1
        Can be used with passportjs for oauth
      • 1
        Yeah
      CONS OF MONGOOSE
      • 3
        Model middleware/hooks are not user friendly

      related Mongoose posts

      Repost

      Overview: To put it simply, we plan to use the MERN stack to build our web application. MongoDB will be used as our primary database. We will use ExpressJS alongside Node.js to set up our API endpoints. Additionally, we plan to use React to build our SPA on the client side and use Redis on the server side as our primary caching solution. Initially, while working on the project, we plan to deploy our server and client both on Heroku . However, Heroku is very limited and we will need the benefits of an Infrastructure as a Service so we will use Amazon EC2 to later deploy our final version of the application.

      Serverside: nodemon will allow us to automatically restart a running instance of our node app when files changes take place. We decided to use MongoDB because it is a non relational database which uses the Document Object Model. This allows a lot of flexibility as compared to a RDMS like SQL which requires a very structural model of data that does not change too much. Another strength of MongoDB is its ease in scalability. We will use Mongoose along side MongoDB to model our application data. Additionally, we will host our MongoDB cluster remotely on MongoDB Atlas. Bcrypt will be used to encrypt user passwords that will be stored in the DB. This is to avoid the risks of storing plain text passwords. Moreover, we will use Cloudinary to store images uploaded by the user. We will also use the Twilio SendGrid API to enable automated emails sent by our application. To protect private API endpoints, we will use JSON Web Token and Passport. Also, PayPal will be used as a payment gateway to accept payments from users.

      Client Side: As mentioned earlier, we will use React to build our SPA. React uses a virtual DOM which is very efficient in rendering a page. Also React will allow us to reuse components. Furthermore, it is very popular and there is a large community that uses React so it can be helpful if we run into issues. We also plan to make a cross platform mobile application later and using React will allow us to reuse a lot of our code with React Native. Redux will be used to manage state. Redux works great with React and will help us manage a global state in the app and avoid the complications of each component having its own state. Additionally, we will use Bootstrap components and custom CSS to style our app.

      Other: Git will be used for version control. During the later stages of our project, we will use Google Analytics to collect useful data regarding user interactions. Moreover, Slack will be our primary communication tool. Also, we will use Visual Studio Code as our primary code editor because it is very light weight and has a wide variety of extensions that will boost productivity. Postman will be used to interact with and debug our API endpoints.

      See more

      Overview: To put it simply, we plan to use the MERN stack to build our web application. MongoDB will be used as our primary database. We will use ExpressJS alongside Node.js to set up our API endpoints. Additionally, we plan to use React to build our SPA on the client side and use Redis on the server side as our primary caching solution. Initially, while working on the project, we plan to deploy our server and client both on Heroku. However, Heroku is very limited and we will need the benefits of an Infrastructure as a Service so we will use Amazon EC2 to later deploy our final version of the application.

      Serverside: nodemon will allow us to automatically restart a running instance of our node app when files changes take place. We decided to use MongoDB because it is a non relational database which uses the Document Object Model. This allows a lot of flexibility as compared to a RDMS like SQL which requires a very structural model of data that does not change too much. Another strength of MongoDB is its ease in scalability. We will use Mongoose along side MongoDB to model our application data. Additionally, we will host our MongoDB cluster remotely on MongoDB Atlas. Bcrypt will be used to encrypt user passwords that will be stored in the DB. This is to avoid the risks of storing plain text passwords. Moreover, we will use Cloudinary to store images uploaded by the user. We will also use the Twilio SendGrid API to enable automated emails sent by our application. To protect private API endpoints, we will use JSON Web Token and Passport. Also, PayPal will be used as a payment gateway to accept payments from users.

      Client Side: As mentioned earlier, we will use React to build our SPA. React uses a virtual DOM which is very efficient in rendering a page. Also React will allow us to reuse components. Furthermore, it is very popular and there is a large community that uses React so it can be helpful if we run into issues. We also plan to make a cross platform mobile application later and using React will allow us to reuse a lot of our code with React Native. Redux will be used to manage state. Redux works great with React and will help us manage a global state in the app and avoid the complications of each component having its own state. Additionally, we will use Bootstrap components and custom CSS to style our app.

      Other: Git will be used for version control. During the later stages of our project, we will use Google Analytics to collect useful data regarding user interactions. Moreover, Slack will be our primary communication tool. Also, we will use Visual Studio Code as our primary code editor because it is very light weight and has a wide variety of extensions that will boost productivity. Postman will be used to interact with and debug our API endpoints.

      See more
      MySQL logo

      MySQL

      87.7K
      71.6K
      3.7K
      The world's most popular open source database
      87.7K
      71.6K
      + 1
      3.7K
      PROS OF MYSQL
      • 793
        Sql
      • 673
        Free
      • 556
        Easy
      • 527
        Widely used
      • 485
        Open source
      • 180
        High availability
      • 160
        Cross-platform support
      • 104
        Great community
      • 78
        Secure
      • 75
        Full-text indexing and searching
      • 25
        Fast, open, available
      • 14
        SSL support
      • 13
        Reliable
      • 13
        Robust
      • 8
        Enterprise Version
      • 7
        Easy to set up on all platforms
      • 2
        NoSQL access to JSON data type
      • 1
        Relational database
      • 1
        Easy, light, scalable
      • 1
        Sequel Pro (best SQL GUI)
      • 1
        Replica Support
      CONS OF MYSQL
      • 14
        Owned by a company with their own agenda
      • 1
        Can't roll back schema changes

      related MySQL posts

      Tim Abbott

      We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

      We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

      And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

      I can't recommend it highly enough.

      See more
      Conor Myhrvold
      Tech Brand Mgr, Office of CTO at Uber · | 21 upvotes · 1.1M views

      Our most popular (& controversial!) article to date on the Uber Engineering blog in 3+ yrs. Why we moved from PostgreSQL to MySQL. In essence, it was due to a variety of limitations of Postgres at the time. Fun fact -- earlier in Uber's history we'd actually moved from MySQL to Postgres before switching back for good, & though we published the article in Summer 2016 we haven't looked back since:

      The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. Specifically, in many of the cases where we previously used Postgres, we now use Schemaless, a novel database sharding layer built on top of MySQL (https://eng.uber.com/schemaless-part-one/). In this article, we’ll explore some of the drawbacks we found with Postgres and explain the decision to build Schemaless and other backend services on top of MySQL:

      https://eng.uber.com/mysql-migration/

      See more
      PostgreSQL logo

      PostgreSQL

      66.9K
      54.4K
      3.5K
      A powerful, open source object-relational database system
      66.9K
      54.4K
      + 1
      3.5K
      PROS OF POSTGRESQL
      • 755
        Relational database
      • 508
        High availability
      • 436
        Enterprise class database
      • 380
        Sql
      • 302
        Sql + nosql
      • 171
        Great community
      • 145
        Easy to setup
      • 129
        Heroku
      • 128
        Secure by default
      • 111
        Postgis
      • 48
        Supports Key-Value
      • 46
        Great JSON support
      • 32
        Cross platform
      • 30
        Extensible
      • 26
        Replication
      • 24
        Triggers
      • 22
        Rollback
      • 21
        Multiversion concurrency control
      • 20
        Open source
      • 17
        Heroku Add-on
      • 14
        Stable, Simple and Good Performance
      • 13
        Powerful
      • 12
        Lets be serious, what other SQL DB would you go for?
      • 9
        Good documentation
      • 7
        Intelligent optimizer
      • 7
        Scalable
      • 6
        Reliable
      • 6
        Transactional DDL
      • 6
        Modern
      • 5
        Free
      • 5
        One stop solution for all things sql no matter the os
      • 4
        Relational database with MVCC
      • 3
        Faster Development
      • 3
        Full-Text Search
      • 3
        Developer friendly
      • 2
        Excellent source code
      • 2
        Great DB for Transactional system or Application
      • 2
        search
      • 1
        Free version
      • 1
        Open-source
      • 1
        Full-text
      • 1
        Text
      CONS OF POSTGRESQL
      • 9
        Table/index bloatings

      related PostgreSQL posts

      Jeyabalaji Subramanian

      Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

      We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

      Based on the above criteria, we selected the following tools to perform the end to end data replication:

      We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

      We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

      In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

      Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

      In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

      See more
      Tim Abbott

      We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

      We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

      And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

      I can't recommend it highly enough.

      See more
      MongoDB logo

      MongoDB

      66.4K
      55.9K
      4.1K
      The database for giant ideas
      66.4K
      55.9K
      + 1
      4.1K
      PROS OF MONGODB
      • 826
        Document-oriented storage
      • 591
        No sql
      • 548
        Ease of use
      • 465
        Fast
      • 407
        High performance
      • 256
        Free
      • 215
        Open source
      • 180
        Flexible
      • 143
        Replication & high availability
      • 110
        Easy to maintain
      • 42
        Querying
      • 38
        Easy scalability
      • 37
        Auto-sharding
      • 36
        High availability
      • 31
        Map/reduce
      • 27
        Document database
      • 25
        Full index support
      • 25
        Easy setup
      • 16
        Reliable
      • 15
        Fast in-place updates
      • 14
        Agile programming, flexible, fast
      • 12
        No database migrations
      • 8
        Enterprise
      • 8
        Easy integration with Node.Js
      • 6
        Enterprise Support
      • 5
        Great NoSQL DB
      • 3
        Drivers support is good
      • 3
        Aggregation Framework
      • 3
        Support for many languages through different drivers
      • 2
        Awesome
      • 2
        Schemaless
      • 2
        Managed service
      • 2
        Fast
      • 2
        Easy to Scale
      • 1
        Consistent
      • 1
        Acid Compliant
      CONS OF MONGODB
      • 5
        Very slowly for connected models that require joins
      • 3
        Not acid compliant
      • 1
        Proprietary query language

      related MongoDB posts

      Jeyabalaji Subramanian

      Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

      We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

      Based on the above criteria, we selected the following tools to perform the end to end data replication:

      We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

      We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

      In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

      Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

      In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

      See more
      Robert Zuber

      We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

      As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

      When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

      See more
      Microsoft SQL Server logo

      Microsoft SQL Server

      13.3K
      10K
      535
      A relational database management system developed by Microsoft
      13.3K
      10K
      + 1
      535
      PROS OF MICROSOFT SQL SERVER
      • 137
        Reliable and easy to use
      • 101
        High performance
      • 94
        Great with .net
      • 65
        Works well with .net
      • 56
        Easy to maintain
      • 21
        Azure support
      • 17
        Always on
      • 17
        Full Index Support
      • 10
        Enterprise manager is fantastic
      • 9
        In-Memory OLTP Engine
      • 2
        Security is forefront
      • 1
        Columnstore indexes
      • 1
        Great documentation
      • 1
        Faster Than Oracle
      • 1
        Decent management tools
      • 1
        Easy to setup and configure
      • 1
        Docker Delivery
      CONS OF MICROSOFT SQL SERVER
      • 4
        Expensive Licensing
      • 2
        Microsoft

      related Microsoft SQL Server posts

      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

      I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

      1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
      2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
      See more
      SQLite logo

      SQLite

      12.5K
      10.1K
      528
      A software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine
      12.5K
      10.1K
      + 1
      528
      PROS OF SQLITE
      • 160
        Lightweight
      • 134
        Portable
      • 121
        Simple
      • 80
        Sql
      • 28
        Preinstalled on iOS and Android
      • 2
        Tcl integration
      • 1
        Free
      • 1
        Telefon
      • 1
        Portable A database on my USB 'love it'
      CONS OF SQLITE
      • 2
        Not for multi-process of multithreaded apps
      • 1
        Needs different binaries for each platform

      related SQLite posts

      Dimelo Waterson
      Shared insights
      on
      PostgreSQLPostgreSQLMySQLMySQLSQLiteSQLite

      I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

      To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

      See more
      Christian Stefanescu
      Head of IT at lawpilots · | 3 upvotes · 17.6K views
      Shared insights
      on
      DjangoDjangoSQLiteSQLitePostgreSQLPostgreSQL

      While I love and use PostgreSQL , I would definitely recommend having a look at SQLite as well. It can be a solid database for lots of applications and it brings some advantages in terms of handling: you don't need a server running, which makes things like testing, deploying or backing up databases much easier. Through the ORM in Django you are one abstraction level away from your database anyway and switching later on is definitely an option, but I believe SQLite is very good for pretty much all the small applications you can think of.

      See more
      MariaDB logo

      MariaDB

      11.6K
      8.8K
      468
      An enhanced, drop-in replacement for MySQL
      11.6K
      8.8K
      + 1
      468
      PROS OF MARIADB
      • 149
        Drop-in mysql replacement
      • 100
        Great performance
      • 74
        Open source
      • 55
        Free
      • 44
        Easy setup
      • 15
        Easy and fast
      • 14
        Lead developer is "monty" widenius the founder of mysql
      • 6
        Also an aws rds service
      • 4
        Learning curve easy
      • 4
        Consistent and robust
      • 2
        Native JSON Support / Dynamic Columns
      • 1
        Real Multi Threaded queries on a table/db
      CONS OF MARIADB
        Be the first to leave a con

        related MariaDB posts

        Joshua Dean Küpper
        CEO at Scrayos UG (haftungsbeschränkt) · | 11 upvotes · 291.9K views

        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. PostgreSQL's 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

        I'm researching what Technology Stack I should use to build my product (something like food delivery App) for Web, iOS, and Android Apps. Please advise which technologies you would recommend from a Scalability, Reliability, Cost, and Efficiency standpoint for a start-up. Here are the technologies I came up with, feel free to suggest any new technology even it's not in the list below.

        For Mobile Apps -

        1. native languages like Swift for IOS and Java/Kotlin for Android
        2. or cross-platform languages like React Native for both IOS and Android Apps

        For UI -

        1. React

        For Back-End or APIs -

        1. Node.js
        2. PHP

        For Database -

        1. PostgreSQL
        2. MySQL
        3. Cloud Firestore
        4. MariaDB

        Thanks!

        See more