Amazon WorkSpaces Streaming Protocol vs Benthos

Overview

Amazon WorkSpaces Streaming Protocol

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Benthos

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Followers8

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Detailed Comparison

Amazon WorkSpaces Streaming Protocol	Benthos
It is a cloud-native streaming protocol that enables a consistent user experience when accessing your end user’s WorkSpaces across global distances and unreliable networks. It also enables additional features such as the beta feature of bi-directional video. As a cloud-native protocol, it delivers feature and performance enhancements without manual updates on your WorkSpaces.	It is a high performance and resilient stream processor, able to connect various sources and sinks in a range of brokering patterns and perform hydration, enrichments, transformations and filters on payloads.
Cloud-native protocol; Consistent user experience; Microservice architecture	Easy to use; Well connected; Create, edit and test configs visually; Reliable and operationally simple
Statistics
Stacks 0	Stacks 5
Followers 2	Followers 8
Votes 0	Votes 0
Integrations
No integrations available	Elasticsearch PostgreSQL Redis MySQL Amazon S3 RabbitMQ Azure Blob Storage Amazon DynamoDB NSQ Google Cloud Pub/Sub

What are some alternatives to Amazon WorkSpaces Streaming Protocol, Benthos?

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

Apache Storm

Apache Storm is a free and open source distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

Confluent

It is a data streaming platform based on Apache Kafka: a full-scale streaming platform, capable of not only publish-and-subscribe, but also the storage and processing of data within the stream

KSQL

KSQL is an open source streaming SQL engine for Apache Kafka. It provides a simple and completely interactive SQL interface for stream processing on Kafka; no need to write code in a programming language such as Java or Python. KSQL is open-source (Apache 2.0 licensed), distributed, scalable, reliable, and real-time.

Heron

Heron is realtime analytics platform developed by Twitter. It is the direct successor of Apache Storm, built to be backwards compatible with Storm's topology API but with a wide array of architectural improvements.

Kafka Streams

It is a client library for building applications and microservices, where the input and output data are stored in Kafka clusters. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka's server-side cluster technology.

Kapacitor

It is a native data processing engine for InfluxDB 1.x and is an integrated component in the InfluxDB 2.0 platform. It can process both stream and batch data from InfluxDB, acting on this data in real-time via its programming language TICKscript.

Redpanda

It is a streaming platform for mission critical workloads. Kafka® compatible, No Zookeeper®, no JVM, and no code changes required. Use all your favorite open source tooling - 10x faster.

Faust

It is a stream processing library, porting the ideas from Kafka Streams to Python. It provides both stream processing and event processing, sharing similarity with tools such as Kafka Streams, Apache Spark/Storm/Samza/Flink.