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What is GlassFlow?

GlassFlow represents a cutting-edge, serverless solution designed for crafting event-driven data pipelines, particularly suited for Python developers. It empowers users to construct real-time data workflows without the burdens typically associated with conventional infrastructure platforms like Kafka or Flink. By simply writing Python functions for data transformations, developers can let GlassFlow manage the underlying infrastructure, which offers advantages such as automatic scaling, low latency, and effective data retention. The platform effortlessly connects with various data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, through its Python SDK and managed connectors. Featuring a low-code interface, it enables users to quickly establish and deploy their data pipelines within minutes. Moreover, GlassFlow is equipped with capabilities like serverless function execution, real-time API connections, alongside alerting and reprocessing functionalities. This suite of features positions GlassFlow as a premier option for Python developers seeking to optimize the creation and oversight of event-driven data pipelines, significantly boosting their productivity and operational efficiency. As the dynamics of data management continue to transform, GlassFlow stands out as an essential instrument in facilitating smoother data processing workflows, thereby catering to the evolving needs of modern developers.

What is Azure Event Hubs?

Event Hubs is a comprehensive managed service designed for the ingestion of real-time data, prioritizing ease of use, dependability, and the ability to scale. It facilitates the streaming of millions of events each second from various sources, enabling the development of agile data pipelines that respond instantly to business challenges. During emergencies, its geo-disaster recovery and geo-replication features ensure continuous data processing. The service integrates seamlessly with other Azure solutions, providing valuable insights for users. Furthermore, existing Apache Kafka clients can connect to Event Hubs without altering their code, allowing a streamlined Kafka experience free from the complexities of cluster management. Users benefit from both real-time data ingestion and microbatching within a single stream, allowing them to focus on deriving insights rather than on infrastructure upkeep. By leveraging Event Hubs, organizations can build robust real-time big data pipelines, swiftly addressing business challenges and maintaining agility in an ever-evolving landscape. This adaptability is crucial for businesses aiming to thrive in today's competitive market.

Media

Media

Integrations Supported

Amazon Kinesis
Apache Flink
Apache Kafka
Ascend
Debezium
Docker
EMnify
Edge Delta
Google Cloud Pub/Sub
Kubernetes
LOGIQ
New Relic
Onum
OpenAI
PeerDB
PubSub+ Platform
Python
Samza
Sclera
Weaviate

Integrations Supported

Amazon Kinesis
Apache Flink
Apache Kafka
Ascend
Debezium
Docker
EMnify
Edge Delta
Google Cloud Pub/Sub
Kubernetes
LOGIQ
New Relic
Onum
OpenAI
PeerDB
PubSub+ Platform
Python
Samza
Sclera
Weaviate

API Availability

Has API

API Availability

Has API

Pricing Information

$350 per month
Free Trial Offered?
Free Version

Pricing Information

$0.03 per hour
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

GlassFlow

Date Founded

2023

Company Location

Germany

Company Website

www.glassflow.dev/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/event-hubs/

Categories and Features

Categories and Features

Streaming Analytics

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

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