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Supabase VS Google Cloud Dataflow

Compare Supabase VS Google Cloud Dataflow and see what are their differences

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Supabase logo Supabase

An open source Firebase alternative

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • Supabase Landing page
    Landing page //
    2023-05-27
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Supabase features and specs

  • Real-time capabilities
    Supabase offers real-time database features that allow you to subscribe to database changes and sync data with your frontend seamlessly.
  • PostgreSQL foundation
    Supabase is built on PostgreSQL, a robust, mature, and highly extensible SQL database, providing strong data integrity and reliability.
  • Open-source
    Supabase is open-source, which means you can inspect, modify, and contribute to the source code. This fosters community engagement and transparency.
  • Ease of use
    Supabase provides an intuitive dashboard and auto-generated APIs, making it easy for developers to manage databases without extensive backend knowledge.
  • Authentication and Authorization
    Supabase includes pre-built authentication and authorization modules, supporting various sign-in methods like email, OAuth, and more, simplifying user management.
  • Scalability
    Supabase is designed to scale with your application, offering plans that can handle from small to large-scale traffic and data operations.

Possible disadvantages of Supabase

  • New and evolving
    As a relatively new platform, Supabase is still evolving, which means it might lack some features found in more mature solutions and could have occasional bugs or stability issues.
  • Limited integration
    Currently, Supabase has fewer third-party integrations compared to other established backend-as-a-service (BaaS) providers, which might limit its utility in diverse tech stacks.
  • Learning curve
    Despite its user-friendly interface, there could be a learning curve for those unfamiliar with PostgreSQL or real-time database concepts.
  • Pricing for advanced features
    While Supabase offers a free tier, advanced features, and higher usage plans come with a cost. This might be limiting for startups or hobby projects with tight budgets.
  • Limited geographic presence
    Supabase's infrastructure might have limited geographic data centers compared to larger cloud providers, potentially affecting latency and performance for users in certain regions.

Google Cloud Dataflow features and specs

  • Scalability
    Google Cloud Dataflow can automatically scale up or down depending on your data processing needs, handling massive datasets with ease.
  • Fully Managed
    Dataflow is a fully managed service, which means you don't have to worry about managing the underlying infrastructure.
  • Unified Programming Model
    It provides a single programming model for both batch and streaming data processing using Apache Beam, simplifying the development process.
  • Integration
    Seamlessly integrates with other Google Cloud services like BigQuery, Cloud Storage, and Bigtable.
  • Real-time Analytics
    Supports real-time data processing, enabling quicker insights and facilitating faster decision-making.
  • Cost Efficiency
    Pay-as-you-go pricing model ensures you only pay for resources you actually use, which can be cost-effective.
  • Global Availability
    Cloud Dataflow is available globally, which allows for regionalized data processing.
  • Fault Tolerance
    Built-in fault tolerance mechanisms help ensure uninterrupted data processing.

Possible disadvantages of Google Cloud Dataflow

  • Steep Learning Curve
    The complexity of using Apache Beam and understanding its model can be challenging for beginners.
  • Debugging Difficulties
    Debugging data processing pipelines can be complex and time-consuming, especially for large-scale data flows.
  • Cost Management
    While it can be cost-efficient, the costs can rise quickly if not monitored properly, particularly with real-time data processing.
  • Vendor Lock-in
    Using Google Cloud Dataflow can lead to vendor lock-in, making it challenging to migrate to another cloud provider.
  • Limited Support for Non-Google Services
    While it integrates well within Google Cloud, support for non-Google services may not be as robust.
  • Latency
    There can be some latency in data processing, especially when dealing with high volumes of data.
  • Complexity in Pipeline Design
    Designing pipelines to be efficient and cost-effective can be complex, requiring significant expertise.

Supabase videos

+ Add

Basic demo

More videos:

  • Review - Supabase in 100 Seconds by Fireship

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to Supabase and Google Cloud Dataflow)

Supabase

Google Cloud Dataflow

Developer Tools
100 100%
Developer Tools
0% 0
Big Data
0 0%
Big Data
100% 100
Realtime Backend / API
100 100%
Realtime Backend / API
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Supabase and Google Cloud Dataflow. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Supabase and Google Cloud Dataflow

Supabase Reviews

10 Top Firebase Alternatives to Ignite Your Development in 2024
Supabase makes it incredibly easy to migrate from Firebase. Its data structure and APIs are designed to feel familiar, so you can switch without a major learning curve. Plus, the open-source nature means you have complete control over your code and data.
Source: genezio.com
Top 7 Firebase Alternatives for App Development in 2024
Community Support and Longevity: Investigate the size and activity of the platform's community. A larger, more active community can provide better support and resources. Platforms like Parse and Supabase have strong community support.
Source: signoz.io
5 Best Vercel Alternatives for Next.js & App Router
Supabase distinguishes itself through its focus on data and community-driven development. Self-hosting capabilities allow you to deploy Supabase's suite of products within your own infrastructure. This maintains data ownership while still leveraging Supabase's tools.
Source: il.ly
Best Serverless Backend Tools of 2023: Pros & Cons, Features & Code Examples
Create an account, a project, and a database. Unlike a NoSQL database like Firebase’s, you need to have a structure ready to be able to manipulate data. But once this step is done―and you’ll have ready-to-use templates to help speed up this part―you can call Supabase like so:
Source: www.rowy.io
2023 Firebase Alternatives: Top 10 Open-Source & Free
Supabase is another trusted platform in our list that calls itself an open-source alternative to Firebase. You can also name it one of the newest cloud service providers similar to Firebase because it launched in 2020. Indeed, with great scalability and documentation support, Supabase could be an ideal option.
Source: digitalcruch.com

Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Based on our record, Supabase seems to be a lot more popular than Google Cloud Dataflow. While we know about 501 links to Supabase, we've tracked only 14 mentions of Google Cloud Dataflow. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Supabase mentions (501)

  • Why devs are quitting aws and what they’re choosing instead
    Platforms like Railway, Render, Fly.io, Vercel, Supabase, and Cloudflare are leading the charge with a shared philosophy:. - Source: dev.to / 11 days ago
  • I analyzed how Supabase and Laravel launched. Here's what I learned.
    Supabase is an open-source alternative to Firebase. They turned fast shipping into a format: launch weeks — announcing something new every day. They were first and initiated a movement. Picture this: according to launchweek.dev, there were 126 launch weeks run by 94 different companies in 2024. - Source: dev.to / about 2 months ago
  • Why You Shouldn’t Invest In Vector Databases?
    In fact, even in the absence of these commercial databases, users can effortlessly install PostgreSQL and leverage its built-in pgvector functionality for vector search. PostgreSQL stands as the benchmark in the realm of open-source databases, offering comprehensive support across various domains of database management. It excels in transaction processing (e.g., CockroachDB), online analytics (e.g., DuckDB),... - Source: dev.to / 26 days ago
  • How to Host a Scalable Full-Stack App for Free Using Cloudflare Pages, Workers, and Supabase
    Create an account at Supabase and create a new project. You’ll get:. - Source: dev.to / 28 days ago
  • Supabase WordPress Integration - SupaWP Plugin
    Supabase provides a robust authentication system supporting email/password, OAuth providers, and magic links. Integrating this with WordPress allows you to leverage Supabase’s secure and scalable auth backend to manage user registration and login seamlessly. - Source: dev.to / about 1 month ago
View more

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 2 years ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 2 years ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 2 years ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 2 years ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 3 years ago
View more

What are some alternatives?

When comparing Supabase and Google Cloud Dataflow, you can also consider the following products

Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Next.js - A small framework for server-rendered universal JavaScript apps

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

AppWrite - Appwrite provides web and mobile developers with a set of easy-to-use and integrate REST APIs to manage their core backend needs.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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