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What is Timeplus?

Timeplus is a robust and user-friendly stream processing platform that combines power with affordability. Packaged as a single binary, it allows for easy deployment across multiple environments. Targeted at data teams in various industries, it facilitates the rapid and intuitive processing of both streaming and historical data. With a streamlined design that eliminates the need for external dependencies, Timeplus provides extensive analytical capabilities for both types of data. Its pricing structure is remarkably economical, costing just a tenth of what comparable open-source solutions demand. Users can effortlessly transform real-time market and transaction data into actionable insights. The platform adeptly supports both append-only and key-value streams, making it particularly suited for financial information monitoring. Moreover, Timeplus simplifies the creation of real-time feature pipelines, enhancing its functionality. It serves as a comprehensive hub for managing all infrastructure logs, metrics, and traces, which are vital for ensuring observability. The user-friendly web console UI accommodates a wide range of data sources, while also allowing data to be pushed via REST API or to create external streams without data duplication. Overall, Timeplus stands out as a versatile and thorough solution for data processing, making it an excellent choice for organizations striving to improve their operational efficiency. Its innovative features set a new standard in stream processing technology.

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

Apache Avro
Apache Kafka
Apache Parquet
Confluent
Docker
JSON
Kubernetes
Python
SQL
Airbyte
Amazon S3
Amazon Web Services (AWS)
Google Cloud Platform
Metabase
Pulsar
Slack
StreamNative

Integrations Supported

Apache Avro
Apache Kafka
Apache Parquet
Confluent
Docker
JSON
Kubernetes
Python
SQL
Amazon Kinesis
Redis
Rust

API Availability

Has API

API Availability

Has API

Pricing Information

$199 per month
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Mac
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Timeplus

Company Website

www.timeplus.com

Company Facts

Organization Name

Arroyo

Company Location

United States

Company Website

www.arroyo.dev/

Categories and Features

Categories and Features

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