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What is Apache Flink?

Apache Flink is a robust framework and distributed processing engine designed for executing stateful computations on both continuous and finite data streams. It has been specifically developed to function effortlessly across different cluster settings, providing computations with remarkable in-memory speed and the ability to scale. Data in various forms is produced as a steady stream of events, which includes credit card transactions, sensor readings, machine logs, and user activities on websites or mobile applications. The strengths of Apache Flink become especially apparent in its ability to manage both unbounded and bounded data sets effectively. Its sophisticated handling of time and state enables Flink's runtime to cater to a diverse array of applications that work with unbounded streams. When it comes to bounded streams, Flink utilizes tailored algorithms and data structures that are optimized for fixed-size data collections, ensuring exceptional performance. In addition, Flink's capability to integrate with various resource managers adds to its adaptability across different computing platforms. As a result, Flink proves to be an invaluable resource for developers in pursuit of efficient and dependable solutions for stream processing, making it a go-to choice in the data engineering landscape.

What is Arroyo?

Scale from zero to millions of events each second with Arroyo, which is provided as a single, efficient binary. It can be executed locally on MacOS or Linux for development needs and can be seamlessly deployed into production via Docker or Kubernetes. Arroyo offers a groundbreaking approach to stream processing that prioritizes the ease of real-time operations over conventional batch processing methods. Designed from the ground up, Arroyo enables anyone with a basic knowledge of SQL to construct reliable, efficient, and precise streaming pipelines. This capability allows data scientists and engineers to build robust real-time applications, models, and dashboards without requiring a specialized team focused on streaming. Users can easily perform operations such as transformations, filtering, aggregation, and data stream joining merely by writing SQL, achieving results in less than a second. Additionally, your streaming pipelines are insulated from triggering alerts simply due to Kubernetes deciding to reschedule your pods. With its ability to function in modern, elastic cloud environments, Arroyo caters to a range of setups from simple container runtimes like Fargate to large-scale distributed systems managed with Kubernetes. This adaptability makes Arroyo the perfect option for organizations aiming to refine their streaming data workflows, ensuring that they can efficiently handle the complexities of real-time data processing. Moreover, Arroyo’s user-friendly design helps organizations streamline their operations significantly, leading to an overall increase in productivity and innovation.

Media

Media

Integrations Supported

Kubernetes
Amazon Managed Service for Apache Flink
Apache Knox
Apache Zeppelin
E-MapReduce
GlassFlow
Hadoop
Hue
IBM Event Automation
StarTree
Streamkap
Warp 10

Integrations Supported

Kubernetes
AWS Fargate
Amazon Kinesis
Apache Avro
Apache Kafka
Apache Parquet
Confluent
JSON
SQL

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Mac
Linux

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

flink.apache.org

Company Facts

Organization Name

Arroyo

Company Location

United States

Company Website

www.arroyo.dev/

Categories and Features

Categories and Features

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