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What is Lenses?

Enable individuals to effectively delve into and assess streaming data. By organizing, documenting, and sharing your data, you could increase productivity by as much as 95%. Once your data is in hand, you can develop applications designed for practical, real-world scenarios. Establish a data-centric security model to tackle the risks linked to open-source technologies, ensuring that data privacy remains a top priority. In addition, provide secure and user-friendly low-code data pipeline options that improve overall usability. Illuminate all hidden facets and deliver unparalleled transparency into your data and applications. Seamlessly integrate your data mesh and technology stack, which empowers you to confidently leverage open-source solutions in live production environments. Lenses has gained recognition as the leading product for real-time stream analytics, as confirmed by independent third-party assessments. With insights collected from our community and extensive engineering efforts, we have crafted features that enable you to focus on what truly adds value from your real-time data. Furthermore, you can deploy and manage SQL-based real-time applications effortlessly across any Kafka Connect or Kubernetes environment, including AWS EKS, simplifying the process of tapping into your data's potential. This approach not only streamlines operations but also opens the door to new avenues for innovation and growth in your organization. By embracing these strategies, you position yourself to thrive in an increasingly data-driven 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

Apache Kafka
Confluent
Kubernetes
Redis
Amazon EKS
Amazon MSK
Amazon S3
Apache Cassandra
Cloudera
Datadog
GitLab
Microsoft Teams
Prometheus

Integrations Supported

Apache Kafka
Confluent
Kubernetes
Redis
AWS Fargate
Amazon Kinesis
Apache Avro
Docker
JSON
Python
SQL

API Availability

API Availability

Has API

Pricing Information

$49 per month

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Lenses.io

Date Founded

2016

Company Location

United Kingdom

Company Website

lenses.io

Company Facts

Organization Name

Arroyo

Company Location

United States

Company Website

www.arroyo.dev/

Categories and Features

Data Governance

Not specified

Data Masking

Not specified

DataOps

Not specified

Streaming Analytics

Not specified

Categories and Features

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