Alternatives to WatermelonDB logo

Alternatives to WatermelonDB

Pouchdb, Realm, RxDB, SQLite, and MySQL are the most popular alternatives and competitors to WatermelonDB.
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What is WatermelonDB and what are its top alternatives?

WatermelonDB is a new way of dealing with user data in React Native and React web apps. It's optimized for building complex applications in React Native, and the number one goal is real-world performance. In simple words, your app must launch fast.
WatermelonDB is a tool in the Databases category of a tech stack.
WatermelonDB is an open source tool with 8.3K GitHub stars and 481 GitHub forks. Here’s a link to WatermelonDB's open source repository on GitHub

Top Alternatives to WatermelonDB

  • Pouchdb
    Pouchdb

    PouchDB enables applications to store data locally while offline, then synchronize it with CouchDB and compatible servers when the application is back online, keeping the user's data in sync no matter where they next login. ...

  • Realm
    Realm

    The Realm Mobile Platform is a next-generation data layer for applications. Realm is reactive, concurrent, and lightweight, allowing you to work with live, native objects. ...

  • RxDB
    RxDB

    💻 📱 Reactive, serverless, client-side, offline-first database in javascript. Client-Side Database for Browsers, NodeJS, electron, cordova, react-native and every other javascript-runtime. ...

  • 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. ...

  • 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. ...

WatermelonDB alternatives & related posts

Pouchdb logo

Pouchdb

116
216
6
Open-source JavaScript database inspired by Apache CouchDB that's designed to run well within the browser
116
216
+ 1
6
PROS OF POUCHDB
  • 2
    Offline cache
  • 1
    JSON
  • 1
    Very fast
  • 1
    Free
  • 1
    Repication
CONS OF POUCHDB
    Be the first to leave a con

    related Pouchdb posts

    Jonathan Pugh
    Software Engineer / Project Manager / Technical Architect · | 25 upvotes · 1.7M views

    I needed to choose a full stack of tools for cross platform mobile application design & development. After much research and trying different tools, these are what I came up with that work for me today:

    For the client coding I chose Framework7 because of its performance, easy learning curve, and very well designed, beautiful UI widgets. I think it's perfect for solo development or small teams. I didn't like React Native. It felt heavy to me and rigid. Framework7 allows the use of #CSS3, which I think is the best technology to come out of the #WWW movement. No other tech has been able to allow designers and developers to develop such flexible, high performance, customisable user interface elements that are highly responsive and hardware accelerated before. Now #CSS3 includes variables and flexboxes it is truly a powerful language and there is no longer a need for preprocessors such as #SCSS / #Sass / #less. React Native contains a very limited interpretation of #CSS3 which I found very frustrating after using #CSS3 for some years already and knowing its powerful features. The other very nice feature of Framework7 is that you can even build for the browser if you want your app to be available for desktop web browsers. The latest release also includes the ability to build for #Electron so you can have MacOS, Windows and Linux desktop apps. This is not possible with React Native yet.

    Framework7 runs on top of Apache Cordova. Cordova and webviews have been slated as being slow in the past. Having a game developer background I found the tweeks to make it run as smooth as silk. One of those tweeks is to use WKWebView. Another important one was using srcset on images.

    I use #Template7 for the for the templating system which is a no-nonsense mobile-centric #HandleBars style extensible templating system. It's easy to write custom helpers for, is fast and has a small footprint. I'm not forced into a new paradigm or learning some new syntax. It operates with standard JavaScript, HTML5 and CSS 3. It's written by the developer of Framework7 and so dovetails with it as expected.

    I configured TypeScript to work with the latest version of Framework7. I consider TypeScript to be one of the best creations to come out of Microsoft in some time. They must have an amazing team working on it. It's very powerful and flexible. It helps you catch a lot of bugs and also provides code completion in supporting IDEs. So for my IDE I use Visual Studio Code which is a blazingly fast and silky smooth editor that integrates seamlessly with TypeScript for the ultimate type checking setup (both products are produced by Microsoft).

    I use Webpack and Babel to compile the JavaScript. TypeScript can compile to JavaScript directly but Babel offers a few more options and polyfills so you can use the latest (and even prerelease) JavaScript features today and compile to be backwards compatible with virtually any browser. My favorite recent addition is "optional chaining" which greatly simplifies and increases readability of a number of sections of my code dealing with getting and setting data in nested objects.

    I use some Ruby scripts to process images with ImageMagick and pngquant to optimise for size and even auto insert responsive image code into the HTML5. Ruby is the ultimate cross platform scripting language. Even as your scripts become large, Ruby allows you to refactor your code easily and make it Object Oriented if necessary. I find it the quickest and easiest way to maintain certain aspects of my build process.

    For the user interface design and prototyping I use Figma. Figma has an almost identical user interface to #Sketch but has the added advantage of being cross platform (MacOS and Windows). Its real-time collaboration features are outstanding and I use them a often as I work mostly on remote projects. Clients can collaborate in real-time and see changes I make as I make them. The clickable prototyping features in Figma are also very well designed and mean I can send clickable prototypes to clients to try user interface updates as they are made and get immediate feedback. I'm currently also evaluating the latest version of #AdobeXD as an alternative to Figma as it has the very cool auto-animate feature. It doesn't have real-time collaboration yet, but I heard it is proposed for 2019.

    For the UI icons I use Font Awesome Pro. They have the largest selection and best looking icons you can find on the internet with several variations in styles so you can find most of the icons you want for standard projects.

    For the backend I was using the #GraphCool Framework. As I later found out, #GraphQL still has some way to go in order to provide the full power of a mature graph query language so later in my project I ripped out #GraphCool and replaced it with CouchDB and Pouchdb. Primarily so I could provide good offline app support. CouchDB with Pouchdb is very flexible and efficient combination and overcomes some of the restrictions I found in #GraphQL and hence #GraphCool also. The most impressive and important feature of CouchDB is its replication. You can configure it in various ways for backups, fault tolerance, caching or conditional merging of databases. CouchDB and Pouchdb even supports storing, retrieving and serving binary or image data or other mime types. This removes a level of complexity usually present in database implementations where binary or image data is usually referenced through an #HTML5 link. With CouchDB and Pouchdb apps can operate offline and sync later, very efficiently, when the network connection is good.

    I use PhoneGap when testing the app. It auto-reloads your app when its code is changed and you can also install it on Android phones to preview your app instantly. iOS is a bit more tricky cause of Apple's policies so it's not available on the App Store, but you can build it and install it yourself to your device.

    So that's my latest mobile stack. What tools do you use? Have you tried these ones?

    See more
    Mike Endale
    Shared insights
    on
    Android SDKAndroid SDKRealmRealmPouchdbPouchdb
    at

    We are building an offline-first Android SDK app. The solution we're working on runs on a mobile device in areas where internet connectivity is intermittent or does not exist. The applications needs to be able to collect data and when it reaches a home base or finds internet connectivity, we'll sync it with the host.

    We've heard Realm and Pouchdb could be a good solution, but we are curious if anyone has any experience with either or have another path forward.

    See more
    Realm logo

    Realm

    224
    372
    16
    Realm makes it easy to build reactive apps, realtime collaborative features, and offline-first experiences.
    224
    372
    + 1
    16
    PROS OF REALM
    • 7
      Good
    • 3
      Elegant API
    • 3
      Cloud Syncing
    • 2
      React Native Support
    • 1
      Strong Adoption Growth
    CONS OF REALM
    • 1
      No offline support for web till now

    related Realm posts

    RxDB logo

    RxDB

    52
    156
    54
    A fast, reactive, client-side database
    52
    156
    + 1
    54
    PROS OF RXDB
    • 14
      Good documentation
    • 12
      Subscription to queries
    • 10
      Works
    • 9
      Example projects
    • 8
      Typescript support
    • 1
      Offline first
    CONS OF RXDB
    • 3
      Bulk operation for updates and other operation

    related RxDB posts

    Gabriel Pa

    If you want to use Pouchdb might as well use RxDB which is an observables wrapper for Pouch but much more comfortable to use. Realm is awesome but Pouchdb and RxDB give you more control. You can use Couchbase (recommended) or CouchDB to enable 2-way sync

    See more
    SQLite logo

    SQLite

    14K
    11.1K
    529
    A software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine
    14K
    11.1K
    + 1
    529
    PROS OF SQLITE
    • 161
      Lightweight
    • 134
      Portable
    • 121
      Simple
    • 80
      Sql
    • 28
      Preinstalled on iOS and Android
    • 2
      Tcl integration
    • 1
      Telefon
    • 1
      Free
    • 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

    Hi all. I want to rewrite my system. I was a complete newbie 4 years ago and have developed a comprehensive business / finance web application that has been running successfully for 3 years (I am a business person and not a developer primarily although it seems I have become a developer). Front-end is written in native PHP (no framework) and jQuery with backend and where many processes run in MySQL. Hosted on Linux and also sends emails with attachments etc. The system logic is great and the business has grown and the system is creaking and needs to be modernised. I feel I would stick with MySql as DB and update / use Django / Spring or Laravel (because its php which I understand). To me, PHP feels old fashioned. I don't mind learning new things and also I want to set the system up that it can be easily migrated to Android/iOS app with SQLite. I would probably employ an experienced developer while also doing some myself. Please provide advice -- from my research it seems Spring/Java is the way to go ... not sure. Thanks

    See more
    MySQL logo

    MySQL

    95.4K
    78.6K
    3.7K
    The world's most popular open source database
    95.4K
    78.6K
    + 1
    3.7K
    PROS OF MYSQL
    • 795
      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
      Robust
    • 13
      Reliable
    • 8
      Enterprise Version
    • 7
      Easy to set up on all platforms
    • 2
      NoSQL access to JSON data type
    • 1
      Replica Support
    • 1
      Relational database
    • 1
      Easy, light, scalable
    • 1
      Sequel Pro (best SQL GUI)
    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 · 1.2M 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

    74.4K
    60.1K
    3.5K
    A powerful, open source object-relational database system
    74.4K
    60.1K
    + 1
    3.5K
    PROS OF POSTGRESQL
    • 754
      Relational database
    • 508
      High availability
    • 436
      Enterprise class database
    • 380
      Sql
    • 303
      Sql + nosql
    • 171
      Great community
    • 145
      Easy to setup
    • 130
      Heroku
    • 128
      Secure by default
    • 112
      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
      Scalable
    • 7
      Intelligent optimizer
    • 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
      search
    • 2
      Great DB for Transactional system or Application
    • 1
      Full-text
    • 1
      Free version
    • 1
      Open-source
    • 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

    72.3K
    61.3K
    4.1K
    The database for giant ideas
    72.3K
    61.3K
    + 1
    4.1K
    PROS OF MONGODB
    • 828
      Document-oriented storage
    • 593
      No sql
    • 549
      Ease of use
    • 465
      Fast
    • 408
      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
      Easy integration with Node.Js
    • 8
      Enterprise
    • 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
    • 6
      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

    15K
    11.1K
    539
    A relational database management system developed by Microsoft
    15K
    11.1K
    + 1
    539
    PROS OF MICROSOFT SQL SERVER
    • 139
      Reliable and easy to use
    • 102
      High performance
    • 95
      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