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Description

Scale from zero to millions of events per second effortlessly. Arroyo is delivered as a single, compact binary, allowing for local development on MacOS or Linux, and seamless deployment to production environments using Docker or Kubernetes. As a pioneering stream processing engine, Arroyo has been specifically designed to simplify real-time processing, making it more accessible than traditional batch processing. Its architecture empowers anyone with SQL knowledge to create dependable, efficient, and accurate streaming pipelines. Data scientists and engineers can independently develop comprehensive real-time applications, models, and dashboards without needing a specialized team of streaming professionals. By employing SQL, users can transform, filter, aggregate, and join data streams, all while achieving sub-second response times. Your streaming pipelines should remain stable and not trigger alerts simply because Kubernetes has chosen to reschedule your pods. Built for modern, elastic cloud infrastructures, Arroyo supports everything from straightforward container runtimes like Fargate to complex, distributed setups on Kubernetes, ensuring versatility and robust performance across various environments. This innovative approach to stream processing significantly enhances the ability to manage data flows in real-time applications.

Description

IBM Streams analyzes a diverse array of streaming data, including unstructured text, video, audio, geospatial data, and sensor inputs, enabling organizations to identify opportunities and mitigate risks while making swift decisions. By leveraging IBM® Streams, users can transform rapidly changing data into meaningful insights. This platform evaluates various forms of streaming data, empowering organizations to recognize trends and threats as they arise. When integrated with other capabilities of IBM Cloud Pak® for Data, which is founded on a flexible and open architecture, it enhances the collaborative efforts of data scientists in developing models to apply to stream flows. Furthermore, it facilitates the real-time analysis of vast datasets, ensuring that deriving actionable value from your data has never been more straightforward. With these tools, organizations can harness the full potential of their data streams for improved outcomes.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS Fargate
Amazon Kinesis
Apache Avro
Apache Flink
Apache Kafka
Apache Parquet
Confluent
Delta Lake
Docker
JSON
Kubernetes
PostgreSQL
Python
Redis
Rust
SQL

Integrations

AWS Fargate
Amazon Kinesis
Apache Avro
Apache Flink
Apache Kafka
Apache Parquet
Confluent
Delta Lake
Docker
JSON
Kubernetes
PostgreSQL
Python
Redis
Rust
SQL

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Arroyo

Country

United States

Website

www.arroyo.dev/

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/cloud/streaming-analytics

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Streaming Analytics

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

Alternatives

Alternatives

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