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Google Cloud Dataflow VS Ably

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

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

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.

Ably logo Ably

The realtime platform that just works. We power more WebSocket connections than any other pub/sub platform, serving over 2 billion devices monthly.
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03
  • Ably Ably homepage
    Ably homepage //
    2024-08-05

We help teams deliver resilient AI UX and high-performance live experiences that stay fast and in sync worldwide. We provide the global realtime layer for AI agents, chat, notifications, live dashboards, and collaboration - engineered to handle peak demand without self-managed infrastructure.

Teams like HubSpot and Intercom use Ably to avoid the cost and complexity of building and operating realtime systems, while still getting predictable performance at serious scale, handling 2T+ API operations per month. Ablyโ€™s Pub/Sub, Chat, and AI Transport products are unified by design, with developer-friendly APIs and SDKs that integrate across your stack.

Google Cloud Dataflow

Website
cloud.google.com
Pricing URL
-
$ Details
-
Release Date
-
Edit details

Ably

Website
ably.com
Pricing URL
Official Ably Pricing
$ Details
freemium
Release Date
2016 January
Startup details
Country
United Kingdom
Founder(s)
Matthew O'Riordan, Dr. Paddy Byers
Employees
50 - 99
Edit details

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.

Ably features and specs

  • Scalability
    Ably is designed to handle a massive number of concurrent connections and messages, making it scalable for both small and large applications.
  • Real-time Messaging
    Ably provides robust real-time messaging capabilities with low latency, supporting use-cases like live chat, gaming, and real-time data streaming.
  • Global Presence
    Ably has a globally distributed network, ensuring low latency and high availability for users around the world.
  • Advanced Features
    It offers advanced features such as message history, presence, and push notifications, which can enhance the functionality of real-time applications.
  • Security
    Ably includes built-in security features such as TLS encryption, token-based authentication, and private channels to ensure secure communication.
  • Extensive Documentation
    The service provides extensive and well-organized documentation, making it easier for developers to integrate and utilize its features.
  • SDKs and Libraries
    Ably offers a wide range of SDKs and libraries for different programming languages and platforms, easing the development process.
  • Reliable Delivery
    It ensures reliable message delivery with features like message queuing and message de-duplication.

Possible disadvantages of Ably

  • Complexity
    Due to its wide range of advanced features, the initial learning curve can be steep for new users.
  • Cost
    For large-scale applications or extensive use of advanced features, the costs can add up, making it potentially expensive.
  • Vendor Lock-in
    Relying heavily on Ablyโ€™s platform-specific features may result in vendor lock-in, making it challenging to switch to other services in the future.
  • Dependence on Internet Connection
    As a cloud-based service, Ablyโ€™s performance is highly dependent on the quality and reliability of the internet connection.
  • Third-party Integration
    While Ably offers various integration options, integrating certain third-party services may require additional custom development or may not be as seamless.

Analysis of Google Cloud Dataflow

Overall verdict

  • Google Cloud Dataflow is a strong choice for users who need a flexible and scalable data processing solution. It is particularly well-suited for real-time and large-scale data processing tasks. However, the best choice ultimately depends on your specific requirements, including cost considerations, existing infrastructure, and technical skills.

Why this product is good

  • Google Cloud Dataflow is a fully managed service for stream and batch data processing. It is based on the Apache Beam model, allowing for a unified data processing approach. It is highly scalable, offers robust integration with other Google Cloud services, and provides powerful data processing capabilities. Its serverless nature means that users do not have to worry about infrastructure management, and it dynamically allocates resources based on the data processing needs.

Recommended for

  • Organizations that require real-time data processing.
  • Projects involving complex data transformations.
  • Users who already utilize Google Cloud Platform and need seamless integration with other Google services.
  • Developers and data engineers familiar with Apache Beam or those willing to learn.

Analysis of Ably

Overall verdict

  • Ably is a reliable and efficient real-time messaging platform, well-suited for applications requiring high performance and scalability. It is generally well-regarded within the developer community for its ease of use and robust feature set.

Why this product is good

  • Features
    Ably provides a comprehensive suite of features such as pub/sub messaging, presence, and history.
  • Security
    It implements robust security practices including TLS encryption, token-based authentication, and private channels.
  • Integration
    Supports numerous protocols and provides SDKs for various programming languages, making it easy to integrate with different systems.
  • Reliability
    Ably offers high availability and low latency, ensuring messages are delivered in real-time.
  • Scalability
    The platform can handle millions of active connections and is designed for horizontal scaling.

Recommended for

  • developers building real-time applications like chat apps, dashboards, or multiplayer games
  • businesses in need of a scalable solution for live updates and notifications
  • teams looking for a platform with strong security and compliance credentials
  • organizations requiring integration with existing development workflows and tools

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

Ably videos

+ Add

How to build a collaborative environment around your product

More videos:

  • Demo - How to build an avatar stack with Ably Spaces
  • Demo - Ably 101: Serverless WebSockets at scale

Category Popularity

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

Google Cloud Dataflow

Ably

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

User comments

Share your experience with using Google Cloud Dataflow and Ably. 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 Google Cloud Dataflow and Ably

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

Ably Reviews

We have no reviews of Ably yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Ably should be more popular than Google Cloud Dataflow. It has been mentiond 26 times since March 2021. 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.

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 3 years ago
  • Hereโ€™s a playlist of 7 hours of music I use to focus when Iโ€™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: almost 4 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: almost 4 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: almost 4 years ago
  • Why we donโ€™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 4 years ago
View more

Ably mentions (26)

  • AWS us-east-1 outage: How Ablyโ€™s multi-region architecture held up
    During this weekโ€™s AWS us-east-1 outage, Ably maintained full service continuity with no customer impact. This was our multi-region architecture working exactly as designed; error rates were negligibly low and unchanged throughout. Any additional round trip latency was limited to 12ms, which is below the typical variance in any client-to-endpoint connection, and well below our 40โ€“50ms global median; this is... - Source: dev.to / 9 months ago
  • Real-Time Sync Alternatives: Vaultrice vs. localStorage, DIY, Firebase, Pusher
    Services like Pusher and Ably are experts in real-time messaging. They provide robust APIs for pub/sub channels, allowing you to broadcast events to clients reliably. - Source: dev.to / 11 months ago
  • CometChat Alternatives โ€“ Comparing the Top 10 Competitors
    Ably is a real-time infrastructure platform that focuses on delivering low-latency, reliable messaging across global distributed systems. It's designed for developers building event-driven applications, including chat, but also supports broader use cases like live dashboards, GPS tracking, and collaborative tools. - Source: dev.to / about 1 year ago
  • Real-Time Authorization in a Chat Application with Permit.io and WebSockets
    For our web socket-based application, weโ€™ll be using Next.js and Ably, a service that allows us to easily integrate and manage real-time capabilities in our apps powered by web socket. - Source: dev.to / over 1 year ago
  • Curiosity: Using Ably.io Realtime Messaging as a Lightweight Database
    Ably offers various solutions for developers, with their most popular being realtime messaging based on the pub/sub model. When you publish a message to a channel, all devices connected to that channel receive it instantly. - Source: dev.to / over 1 year ago
View more

What are some alternatives?

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

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

Pusher - Pusher is a hosted API for quickly, easily and securely adding scalable realtime functionality via WebSockets to web and mobile apps.

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

Socket.io - Realtime application framework (Node.JS server)

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

PubNub - PubNub is a real-time messaging system for web and mobile apps that can handle API for all platforms and push messages to any device anywhere in the world in a fraction of a second without having to worry about proxies, firewalls or mobile drop-offs.

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