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Description

Fastly’s Compute@Edge platform empowers developers to create high-performance, globally distributed applications while seamlessly executing code at the edge, all without the burden of managing the infrastructure underneath. You can implement intricate logic for any application or backend service utilizing our efficient, secure, and scalable serverless computing model. With Compute@Edge, experience an astonishing 100x improvement in code execution startup times compared to other serverless options. Your code runs concurrently across numerous servers situated worldwide, eliminating issues like cold starts or roundtrip delays, ensuring a consistently fast computing experience. This approach prioritizes enhanced user experiences, a key aspect of digital transformation. You can effortlessly write, deploy, and test your code at the Fastly edge using a robust local development and debugging environment. Additionally, we take care of all the necessary components to ensure your application scales rapidly and globally, positioning it as close to your end users as possible. Ultimately, this enables you to focus on innovation while we handle the complexities of deployment and scaling.

Description

GlassFlow is an innovative, serverless platform for building event-driven data pipelines, specifically tailored for developers working with Python. It allows users to create real-time data workflows without the complexities associated with traditional infrastructure solutions like Kafka or Flink. Developers can simply write Python functions to specify data transformations, while GlassFlow takes care of the infrastructure, providing benefits such as automatic scaling, low latency, and efficient data retention. The platform seamlessly integrates with a variety of data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, utilizing its Python SDK and managed connectors. With a low-code interface, users can rapidly set up and deploy their data pipelines in a matter of minutes. Additionally, GlassFlow includes functionalities such as serverless function execution, real-time API connections, as well as alerting and reprocessing features. This combination of capabilities makes GlassFlow an ideal choice for Python developers looking to streamline the development and management of event-driven data pipelines, ultimately enhancing their productivity and efficiency. As the data landscape continues to evolve, GlassFlow positions itself as a pivotal tool in simplifying data processing workflows.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Kinesis No 
Apache Flink No 
Apache Kafka No 
Debezium No 
Docker No 
Fastly Yes 
Google Cloud Pub/Sub No 
JSON No 
JavaScript Yes 
Kubernetes No 
OpenAI No 
Python No 
Terraform Yes 

Integrations

Amazon Kinesis Yes 
Apache Flink Yes 
Apache Kafka Yes 
Debezium Yes 
Docker Yes 
Fastly No 
Google Cloud Pub/Sub Yes 
JSON Yes 
JavaScript No 
Kubernetes Yes 
OpenAI Yes 
Python Yes 
Terraform No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$350 per month
Free Trial Yes 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Fastly

Founded

2011

Country

United States

Website

www.fastly.com/products/edge-compute

Vendor Details

Company Name

GlassFlow

Founded

2023

Country

Germany

Website

www.glassflow.dev/

Product Features

Product Features

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Alternatives

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