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What is Yandex Data Streams?

Enables efficient data interchange among various elements within microservice frameworks. When employed as a communication strategy for microservices, it not only simplifies integration processes but also boosts both reliability and scalability. This system facilitates almost instantaneous data reading and writing while allowing users to adjust data throughput and retention periods based on unique requirements. Users have the ability to meticulously tailor resources for processing data streams, which can range from small streams of 100 KB/s to larger ones reaching 100 MB/s. Moreover, Yandex Data Transfer supports the distribution of a single stream to multiple destinations, each with its own retention policies. The architecture guarantees that data is automatically replicated across numerous geographically diverse availability zones, providing both redundancy and easy access. After the setup phase, users can centrally manage data streams via the management console or API, ensuring streamlined oversight. The platform also accommodates ongoing data collection from a wide range of sources, such as browsing histories and application logs, which makes it an adaptable solution for real-time analytics. In summary, Yandex Data Streams excels in its ability to meet diverse data ingestion requirements across a variety of platforms, making it an essential tool for modern data-driven applications. Additionally, its capacity for real-time processing and seamless integration further solidifies its position as a leader in the field of data management solutions.

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.

Media

Media

Integrations Supported

Amazon Kinesis
Amazon S3
Apache Kafka
Yandex Cloud
Yandex Data Transfer

Integrations Supported

Amazon Managed Service for Apache Flink
Apache Doris
Apache Hudi
Apache Iceberg
Apache Mesos
Arroyo
DeltaStream
E-MapReduce
GlassFlow
Hadoop
IBM Event Automation
Netdata
VeloDB
Ververica
Warp 10

API Availability

Has API

API Availability

Has API

Pricing Information

$0.086400 per GB
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Yandex

Date Founded

1997

Company Location

Russia

Company Website

cloud.yandex.com/en/services/data-streams

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

flink.apache.org

Categories and Features

Data Exchange

Not specified

Categories and Features

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