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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.

What is AWS Batch?

AWS Batch offers a convenient and efficient platform for developers, scientists, and engineers to manage a large number of batch computing tasks within the AWS ecosystem. It automatically determines the optimal amount and type of computing resources, such as CPU- or memory-optimized instances, based on the specific requirements and scale of the submitted jobs. This functionality allows users to avoid the difficulties of installing or maintaining batch computing software and server infrastructure, enabling them to focus on analyzing results and solving problems. With the ability to plan, schedule, and execute batch workloads, AWS Batch utilizes the full range of AWS compute services, including AWS Fargate, Amazon EC2, and Spot Instances. Notably, AWS Batch does not impose any additional charges; users are only billed for the AWS resources they use, such as EC2 instances or Fargate tasks, to run and store their batch jobs. This smart resource allocation not only conserves time but also minimizes operational burdens for organizations, fostering greater productivity and efficiency in their computing processes. Ultimately, AWS Batch empowers users to harness cloud computing capabilities without the typical hassles of resource management.

Media

Media

Integrations Supported

AWS Fargate
AWS ParallelCluster
AWS Secrets Manager
Amazon EC2 P4 Instances
Amazon EC2 Trn2 Instances
Amazon Fresh
Amazon Kinesis
Amazon Linux 2
Apache Parquet
BMC AMI Ops Automation for Capping
Confluent
EC2 Spot
Flyte
Kubernetes
PostgreSQL
Redis
Rust
SQL
Saagie

Integrations Supported

AWS Fargate
AWS ParallelCluster
AWS Secrets Manager
Amazon EC2 P4 Instances
Amazon EC2 Trn2 Instances
Amazon Fresh
Amazon Kinesis
Amazon Linux 2
Apache Parquet
BMC AMI Ops Automation for Capping
Confluent
EC2 Spot
Flyte
Kubernetes
PostgreSQL
Redis
Rust
SQL
Saagie

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Arroyo

Company Location

United States

Company Website

www.arroyo.dev/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/batch/

Categories and Features

DevOps

Approval Workflow
Dashboard
KPIs
Policy Management
Portfolio Management
Prioritization
Release Management
Timeline Management
Troubleshooting Reports

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Popular Alternatives

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