Alternatives to FaunaDB logo

Alternatives to FaunaDB

Firebase, CockroachDB, Cassandra, MongoDB, and FoundationDB are the most popular alternatives and competitors to FaunaDB.
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What is FaunaDB and what are its top alternatives?

FaunaDB is a global serverless database that gives you ubiquitous, low latency access to app data, without sacrificing data correctness and scale. It eliminates layers of app code for manually handling data anomalies, security, and scale, creating a friendlier dev experience for you and better app experience for your users.
FaunaDB is a tool in the Databases category of a tech stack.

Top Alternatives to FaunaDB

  • Firebase

    Firebase

    Firebase is a cloud service designed to power real-time, collaborative applications. Simply add the Firebase library to your application to gain access to a shared data structure; any changes you make to that data are automatically synchronized with the Firebase cloud and with other clients within milliseconds. ...

  • CockroachDB

    CockroachDB

    It allows you to deploy a database on-prem, in the cloud or even across clouds, all as a single store. It is a simple and straightforward bridge to your future, cloud-based data architecture. ...

  • Cassandra

    Cassandra

    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL. ...

  • 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. ...

  • FoundationDB

    FoundationDB

    FoundationDB is a NoSQL database with a shared nothing architecture. Designed around a "core" ordered key-value database, additional features and data models are supplied in layers. The key-value database, as well as all layers, supports full, cross-key and cross-server ACID transactions. ...

  • Hasura

    Hasura

    An open source GraphQL engine that deploys instant, realtime GraphQL APIs on any Postgres database. ...

  • Prisma

    Prisma

    Prisma is an open-source database toolkit. It replaces traditional ORMs and makes database access easy with an auto-generated query builder for TypeScript & Node.js. ...

  • 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. ...

FaunaDB alternatives & related posts

Firebase logo

Firebase

27.2K
22.9K
1.9K
The Realtime App Platform
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PROS OF FIREBASE
  • 361
    Realtime backend made easy
  • 264
    Fast and responsive
  • 234
    Easy setup
  • 207
    Real-time
  • 186
    JSON
  • 127
    Free
  • 121
    Backed by google
  • 81
    Angular adaptor
  • 63
    Reliable
  • 36
    Great customer support
  • 26
    Great documentation
  • 23
    Real-time synchronization
  • 20
    Mobile friendly
  • 17
    Rapid prototyping
  • 12
    Great security
  • 11
    Automatic scaling
  • 10
    Freakingly awesome
  • 8
    Chat
  • 8
    Angularfire is an amazing addition!
  • 8
    Super fast development
  • 6
    Awesome next-gen backend
  • 6
    Ios adaptor
  • 5
    Built in user auth/oauth
  • 5
    Firebase hosting
  • 4
    Speed of light
  • 4
    Very easy to use
  • 3
    It's made development super fast
  • 3
    Great
  • 3
    Brilliant for startups
  • 2
    Great all-round functionality
  • 2
    Low battery consumption
  • 2
    I can quickly create static web apps with no backend
  • 2
    The concurrent updates create a great experience
  • 2
    JS Offline and Sync suport
  • 1
    Faster workflow
  • 1
    Large
  • 1
    Serverless
  • 1
    .net
  • 1
    Free SSL
  • 1
    Good Free Limits
  • 1
    Push notification
  • 1
    Easy to use
  • 1
    Easy Reactjs integration
CONS OF FIREBASE
  • 28
    Can become expensive
  • 15
    Scalability is not infinite
  • 14
    No open source, you depend on external company
  • 9
    Not Flexible Enough
  • 5
    Cant filter queries
  • 3
    Very unstable server
  • 2
    Too many errors
  • 2
    No Relational Data

related Firebase posts

Stephen Gheysens
Senior Solutions Engineer at Twilio · | 14 upvotes · 295.4K views

Hi Otensia! I'd definitely recommend using the skills you've already got and building with JavaScript is a smart way to go these days. Most platform services have JavaScript/Node SDKs or NPM packages, many serverless platforms support Node in case you need to write any backend logic, and JavaScript is incredibly popular - meaning it will be easy to hire for, should you ever need to.

My advice would be "don't reinvent the wheel". If you already have a skill set that will work well to solve the problem at hand, and you don't need it for any other projects, don't spend the time jumping into a new language. If you're looking for an excuse to learn something new, it would be better to invest that time in learning a new platform/tool that compliments your knowledge of JavaScript. For this project, I might recommend using Netlify, Vercel, or Google Firebase to quickly and easily deploy your web app. If you need to add user authentication, there are great examples out there for Firebase Authentication, Auth0, or even Magic (a newcomer on the Auth scene, but very user friendly). All of these services work very well with a JavaScript-based application.

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Tassanai Singprom

This is my stack in Application & Data

JavaScript PHP HTML5 jQuery Redis Amazon EC2 Ubuntu Sass Vue.js Firebase Laravel Lumen Amazon RDS GraphQL MariaDB

My Utilities Tools

Google Analytics Postman Elasticsearch

My Devops Tools

Git GitHub GitLab npm Visual Studio Code Kibana Sentry BrowserStack

My Business Tools

Slack

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CockroachDB logo

CockroachDB

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225
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A cloud-native SQL database for building global, scalable cloud services that survive disasters.
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PROS OF COCKROACHDB
    Be the first to leave a pro
    CONS OF COCKROACHDB
      Be the first to leave a con

      related CockroachDB posts

      Cassandra logo

      Cassandra

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      A partitioned row store. Rows are organized into tables with a required primary key.
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      PROS OF CASSANDRA
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        Distributed
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        High performance
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        High availability
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        Easy scalability
      • 52
        Replication
      • 26
        Reliable
      • 26
        Multi datacenter deployments
      • 8
        OLTP
      • 7
        Schema optional
      • 6
        Open source
      • 2
        Workload separation (via MDC)
      CONS OF CASSANDRA
      • 2
        Reliability of replication
      • 1
        Updates

      related Cassandra posts

      Thierry Schellenbach
      Shared insights
      on
      Redis
      Cassandra
      RocksDB
      at

      1.0 of Stream leveraged Cassandra for storing the feed. Cassandra is a common choice for building feeds. Instagram, for instance started, out with Redis but eventually switched to Cassandra to handle their rapid usage growth. Cassandra can handle write heavy workloads very efficiently.

      Cassandra is a great tool that allows you to scale write capacity simply by adding more nodes, though it is also very complex. This complexity made it hard to diagnose performance fluctuations. Even though we had years of experience with running Cassandra, it still felt like a bit of a black box. When building Stream 2.0 we decided to go for a different approach and build Keevo. Keevo is our in-house key-value store built upon RocksDB, gRPC and Raft.

      RocksDB is a highly performant embeddable database library developed and maintained by Facebook’s data engineering team. RocksDB started as a fork of Google’s LevelDB that introduced several performance improvements for SSD. Nowadays RocksDB is a project on its own and is under active development. It is written in C++ and it’s fast. Have a look at how this benchmark handles 7 million QPS. In terms of technology it’s much more simple than Cassandra.

      This translates into reduced maintenance overhead, improved performance and, most importantly, more consistent performance. It’s interesting to note that LinkedIn also uses RocksDB for their feed.

      #InMemoryDatabases #DataStores #Databases

      See more
      Umair Iftikhar
      Technical Architect at Vappar · | 3 upvotes · 119.7K views

      Developing a solution that collects Telemetry Data from different devices, nearly 1000 devices minimum and maximum 12000. Each device is sending 2 packets in 1 second. This is time-series data, and this data definition and different reports are saved on PostgreSQL. Like Building information, maintenance records, etc. I want to know about the best solution. This data is required for Math and ML to run different algorithms. Also, data is raw without definitions and information stored in PostgreSQL. Initially, I went with TimescaleDB due to PostgreSQL support, but to increase in sites, I started facing many issues with timescale DB in terms of flexibility of storing data.

      My major requirement is also the replication of the database for reporting and different purposes. You may also suggest other options other than Druid and Cassandra. But an open source solution is appreciated.

      See more
      MongoDB logo

      MongoDB

      62.5K
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      The database for giant ideas
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      PROS OF MONGODB
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        Document-oriented storage
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        No sql
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        Ease of use
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        Fast
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        High performance
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        Free
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        Open source
      • 179
        Flexible
      • 142
        Replication & high availability
      • 109
        Easy to maintain
      • 41
        Querying
      • 37
        Easy scalability
      • 36
        Auto-sharding
      • 35
        High availability
      • 31
        Map/reduce
      • 26
        Document database
      • 24
        Easy setup
      • 24
        Full index support
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        Reliable
      • 14
        Fast in-place updates
      • 13
        Agile programming, flexible, fast
      • 11
        No database migrations
      • 7
        Enterprise
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        Easy integration with Node.Js
      • 5
        Enterprise Support
      • 4
        Great NoSQL DB
      • 3
        Aggregation Framework
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        Support for many languages through different drivers
      • 3
        Drivers support is good
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        Schemaless
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        Fast
      • 2
        Awesome
      • 2
        Managed service
      • 2
        Easy to Scale
      • 1
        Consistent
      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
      FoundationDB logo

      FoundationDB

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      Multi-model database with particularly strong fault tolerance, performance, and operational ease
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      PROS OF FOUNDATIONDB
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        ACID transactions
      • 4
        Linear scalability
      • 3
        Multi-model database
      • 3
        Key-Value Store
      • 3
        Great Foundation
      • 1
        SQL Layer
      CONS OF FOUNDATIONDB
        Be the first to leave a con

        related FoundationDB posts

        Hasura logo

        Hasura

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        An open source GraphQL engine that deploys instant, realtime GraphQL APIs on any Postgres database.
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        PROS OF HASURA
        • 20
          Fast
        • 16
          Easy GraphQL subscriptions
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          Easy setup of relationships and permissions
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          Automatically generates your GraphQL schema
        • 13
          Minimal learning curve
        • 12
          No back-end code required
        • 11
          Works with new and existing databases
        • 10
          Instant production ready GraphQL
        • 10
          Great UX
        • 3
          Simple
        • 2
          Low usage of resources
        CONS OF HASURA
        • 2
          Cumbersome validations

        related Hasura posts

        Prisma logo

        Prisma

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        Modern Database Access for TypeScript & Node.js
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        PROS OF PRISMA
        • 9
          Type-safe database access
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          Open Source
        • 7
          Auto-generated query builder
        • 6
          Increases confidence during development
        • 4
          Built specifically for Postgres and TypeScript
        • 4
          Supports multible database systems
        • 4
          Productive application development
        • 0
          Supports multible RDBMSs
        • 0
          Robust migrations system
        CONS OF PRISMA
        • 1
          Doesn't support downward/back migrations

        related Prisma posts

        Divine Bawa
        at PayHub Ghana Limited · | 16 upvotes · 296K views

        I just finished a web app meant for a business that offers training programs for certain professional courses. I chose this stack to test out my skills in graphql and react. I used Node.js , GraphQL , MySQL for the #Backend utilizing Prisma as a database interface for MySQL to provide CRUD APIs and graphql-yoga as a server. For the #frontend I chose React, styled-components for styling, Next.js for routing and SSR and Apollo for data management. I really liked the outcome and I will definitely use this stack in future projects.

        See more
        Munkhtegsh Munkhbat
        Software Engineer Consultant at LoanSnap · | 9 upvotes · 127.4K views

        In my last side project, I built a web posting application that has similar features as Facebook and hosted on Heroku. The user can register an account, create posts, upload images and share with others. I took an advantage of graphql-subscriptions to handle realtime notifications in the comments section. Currently, I'm at the last stage of styling and building layouts.

        For the #Backend I used graphql-yoga, Prisma, GraphQL with PostgreSQL database. For the #FrontEnd: React, styled-components with Apollo. The app is hosted on Heroku.

        See more
        MySQL logo

        MySQL

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        The world's most popular open source database
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        PROS OF MYSQL
        • 791
          Sql
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          Free
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          Easy
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          Widely used
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          Open source
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          High availability
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          Cross-platform support
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          Great community
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          Secure
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          Full-text indexing and searching
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          Fast, open, available
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          SSL support
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          Robust
        • 13
          Reliable
        • 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