Alternatives to CloudBoost logo

Alternatives to CloudBoost

Firebase, Parse, Amazon DynamoDB, Cloud Firestore, and Azure Cosmos DB are the most popular alternatives and competitors to CloudBoost.
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What is CloudBoost and what are its top alternatives?

CloudBoost.io is a database service for the “next web” - that not only does data-storage, but also search, real-time and a whole lot more which enables developers to build much richer apps with 50% less time saving them a ton of cost and helping them go to market much faster.
CloudBoost is a tool in the NoSQL Database as a Service category of a tech stack.

Top Alternatives to CloudBoost

  • 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. ...

  • Parse

    Parse

    With Parse, you can add a scalable and powerful backend in minutes and launch a full-featured app in record time without ever worrying about server management. We offer push notifications, social integration, data storage, and the ability to add rich custom logic to your app’s backend with Cloud Code. ...

  • Amazon DynamoDB

    Amazon DynamoDB

    With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use. ...

  • Cloud Firestore

    Cloud Firestore

    Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale. ...

  • Azure Cosmos DB

    Azure Cosmos DB

    Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development. ...

  • Google Cloud Datastore

    Google Cloud Datastore

    Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries. ...

  • Google Cloud Bigtable

    Google Cloud Bigtable

    Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail. ...

  • Firebase Realtime Database

    Firebase Realtime Database

    It is a cloud-hosted NoSQL database that lets you store and sync data between your users in realtime. Data is synced across all clients in realtime, and remains available when your app goes offline. ...

CloudBoost alternatives & related posts

Firebase logo

Firebase

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18.6K
1.9K
The Realtime App Platform
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PROS OF FIREBASE
  • 357
    Realtime backend made easy
  • 261
    Fast and responsive
  • 233
    Easy setup
  • 206
    Real-time
  • 184
    JSON
  • 126
    Free
  • 120
    Backed by google
  • 80
    Angular adaptor
  • 62
    Reliable
  • 36
    Great customer support
  • 25
    Great documentation
  • 22
    Real-time synchronization
  • 19
    Mobile friendly
  • 17
    Rapid prototyping
  • 12
    Great security
  • 10
    Automatic scaling
  • 9
    Freakingly awesome
  • 8
    Super fast development
  • 8
    Chat
  • 8
    Angularfire is an amazing addition!
  • 6
    Awesome next-gen backend
  • 6
    Ios adaptor
  • 5
    Firebase hosting
  • 5
    Built in user auth/oauth
  • 4
    Very easy to use
  • 3
    Great
  • 3
    Speed of light
  • 3
    Brilliant for startups
  • 3
    It's made development super fast
  • 2
    Low battery consumption
  • 2
    The concurrent updates create a great experience
  • 2
    I can quickly create static web apps with no backend
  • 2
    Great all-round functionality
  • 1
    Easy Reactjs integration
  • 1
    Good Free Limits
  • 1
    .net
  • 1
    Faster workflow
  • 1
    Serverless
  • 1
    JS Offline and Sync suport
  • 1
    Easy to use
  • 1
    Large
  • 1
    Push notification
CONS OF FIREBASE
  • 26
    Can become expensive
  • 14
    No open source, you depend on external company
  • 14
    Scalability is not infinite
  • 9
    Not Flexible Enough
  • 5
    Cant filter queries
  • 3
    Very unstable server
  • 2
    Too many errors
  • 2
    No Relational Data

related Firebase posts

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

See more

We are starting to work on a web-based platform aiming to connect artists (clients) and professional freelancers (service providers). In-app, timeline-based, real-time communication between users (& storing it), file transfers, and push notifications are essential core features. We are considering using Node.js, ExpressJS, React, MongoDB stack with Socket.IO & Apollo, or maybe using Real-Time Database and functionalities of Firebase.

See more
Parse logo

Parse

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The complete mobile app platform
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PROS OF PARSE
  • 115
    Easy setup
  • 75
    Free hosting
  • 61
    Well-documented
  • 48
    Cheap
  • 46
    Use push notifications in 3 lines of code
  • 40
    Fast
  • 38
    Cloud code
  • 31
    Good for prototypes
  • 30
    Cloud modules
  • 27
    Backed by facebook
  • 7
    Parse Push
  • 6
    Cross Platform
  • 6
    Parse Core
  • 6
    Parse Analytics
  • 5
    Multiplatform
  • 5
    Quick chat and profile capabilities
  • 5
    Free Tier
  • 4
    Cloud Based
  • 3
    Geopoints
  • 3
    Free
  • 3
    Backend as a service
  • 3
    Backbone Models
  • 3
    Nice security concept
  • 2
    Local Datastore
  • 2
    Anonymous Users
  • 2
    Easy to use
  • 1
    About to Die
CONS OF PARSE
    Be the first to leave a con

    related Parse posts

    Amazon DynamoDB logo

    Amazon DynamoDB

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    Fully managed NoSQL database service
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    PROS OF AMAZON DYNAMODB
    • 62
      Predictable performance and cost
    • 56
      Scalable
    • 35
      Native JSON Support
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      AWS Free Tier
    • 7
      Fast
    • 3
      No sql
    • 3
      To store data
    • 2
      Serverless
    • 2
      No Stored procedures is GOOD
    • 1
      ORM with DynamoDBMapper
    • 1
      Elastic Scalability using on-demand mode
    • 1
      Elastic Scalability using autoscaling
    • 1
      DynamoDB Stream
    CONS OF AMAZON DYNAMODB
    • 3
      Only sequential access for paginate data

    related Amazon DynamoDB posts

    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 2.2M views

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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    Dmitry Mukhin

    Uploadcare has built an infinitely scalable infrastructure by leveraging AWS. Building on top of AWS allows us to process 350M daily requests for file uploads, manipulations, and deliveries. When we started in 2011 the only cloud alternative to AWS was Google App Engine which was a no-go for a rather complex solution we wanted to build. We also didn’t want to buy any hardware or use co-locations.

    Our stack handles receiving files, communicating with external file sources, managing file storage, managing user and file data, processing files, file caching and delivery, and managing user interface dashboards.

    At its core, Uploadcare runs on Python. The Europython 2011 conference in Florence really inspired us, coupled with the fact that it was general enough to solve all of our challenges informed this decision. Additionally we had prior experience working in Python.

    We chose to build the main application with Django because of its feature completeness and large footprint within the Python ecosystem.

    All the communications within our ecosystem occur via several HTTP APIs, Redis, Amazon S3, and Amazon DynamoDB. We decided on this architecture so that our our system could be scalable in terms of storage and database throughput. This way we only need Django running on top of our database cluster. We use PostgreSQL as our database because it is considered an industry standard when it comes to clustering and scaling.

    See more
    Cloud Firestore logo

    Cloud Firestore

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    NoSQL database built for global apps
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    PROS OF CLOUD FIRESTORE
    • 12
      Cloud Storage
    • 12
      Easy to use
    • 10
      Realtime Database
    • 10
      Easy setup
    • 8
      Super fast
    • 6
      Authentication
    • 6
      Realtime listeners
    • 5
      Could Messaging
    • 4
      Google Analytics integration
    • 3
      Adwords, Admob integration
    • 3
      Performance Monitoring
    • 3
      Crash Reporting
    • 3
      Hosting
    • 3
      Test Lab for Android
    • 3
      Sharing App via invites
    • 2
      Dynamic Links (Deeplinking support)
    • 0
      Robust ALI
    CONS OF CLOUD FIRESTORE
    • 6
      Doesn't support FullTextSearch natively

    related Cloud Firestore posts

    Fontumi focuses on the development of telecommunications solutions. We have opted for technologies that allow agile development and great scalability.

    Firebase and Node.js + FeathersJS are technologies that we have used on the server side. Vue.js is our main framework for clients.

    Our latest products launched have been focused on the integration of AI systems for enriched conversations. Google Compute Engine , along with Dialogflow and Cloud Firestore have been important tools for this work.

    Git + GitHub + Visual Studio Code is a killer stack.

    See more

    We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

    See more
    Azure Cosmos DB logo

    Azure Cosmos DB

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    A fully-managed, globally distributed NoSQL database service
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    PROS OF AZURE COSMOS DB
    • 26
      Best-of-breed NoSQL features
    • 19
      High scalability
    • 14
      Globally distributed
    • 13
      Automatic indexing over flexible json data model
    • 9
      Tunable consistency
    • 9
      Always on with 99.99% availability sla
    • 6
      Javascript language integrated transactions and queries
    • 5
      Predictable performance
    • 4
      High performance
    • 4
      Analytics Store
    • 1
      No Sql
    • 1
      Rapid Development
    • 1
      Auto Indexing
    • 1
      Ease of use
    CONS OF AZURE COSMOS DB
    • 15
      Pricing
    • 3
      Poor No SQL query support

    related Azure Cosmos DB posts

    We have an in-house build experiment management system. We produce samples as input to the next step, which then could produce 1 sample(1-1) and many samples (1 - many). There are many steps like this. So far, we are tracking genealogy (limited tracking) in the MySQL database, which is becoming hard to trace back to the original material or sample(I can give more details if required). So, we are considering a Graph database. I am requesting advice from the experts.

    1. Is a graph database the right choice, or can we manage with RDBMS?
    2. If RDBMS, which RDMS, which feature, or which approach could make this manageable or sustainable
    3. If Graph database(Neo4j, OrientDB, Azure Cosmos DB, Amazon Neptune, ArangoDB), which one is good, and what are the best practices?

    I am sorry that this might be a loaded question.

    See more

    Hi Mohamad, out of these two options, I'd recommend starting with MongoDB (on MongoDB Atlas) for a few reasons:

    • Open Source & Portability - With MongoDB being open source, you have transparency into how your system will work. Not only can you see how it works, but you later have the option to migrate to self-hosted versions of the platform (decreasing costs and avoiding vendor lock-in) or move to a Mongo-compatible hosted database like Amazon DocumentDB or Azure Cosmos DB.

    • Querying & Aggregation - MongoDB has been around a few years longer than Firebase, and in my opinion, that is evident from the great design and flexibility of APIs you have for querying and aggregating data.

    • Tooling - MongoDB Atlas monitoring tools and the Compass GUI are great for understanding and interacting with the data in your database as you're growing your platform.

    I hope this helps!

    See more
    Google Cloud Datastore logo

    Google Cloud Datastore

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    A Fully Managed NoSQL Data Storage Service
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    PROS OF GOOGLE CLOUD DATASTORE
    • 7
      High scalability
    • 2
      Serverless
    • 2
      Ability to query any property
    • 1
      Pay for what you use
    CONS OF GOOGLE CLOUD DATASTORE
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      related Google Cloud Datastore posts

      Google Cloud Bigtable logo

      Google Cloud Bigtable

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      The same database that powers Google Search, Gmail and Analytics
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      PROS OF GOOGLE CLOUD BIGTABLE
      • 8
        High performance
      • 7
        Fully managed
      • 5
        High scalability
      CONS OF GOOGLE CLOUD BIGTABLE
        Be the first to leave a con

        related Google Cloud Bigtable posts

        Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

        Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

        Check Out My Architecture: CLICK ME

        Check out the GitHub repo attached

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        Firebase Realtime Database logo

        Firebase Realtime Database

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        Store and sync data in real time
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        PROS OF FIREBASE REALTIME DATABASE
        • 1
          Very fast
        CONS OF FIREBASE REALTIME DATABASE
        • 1
          Poor query

        related Firebase Realtime Database posts

        We are building a social media app, where users will post images, like their post, and make friends based on their interest. We are currently using Cloud Firestore and Firebase Realtime Database. We are looking for another database like Amazon DynamoDB; how much this decision can be efficient in terms of pricing and overhead?

        See more