Spark Streaming

Spark Streaming

Apache Software Foundation
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About

Scale from zero to millions of events per second. Arroyo ships as a single, compact binary. Run locally on MacOS or Linux for development, and deploy to production with Docker or Kubernetes. Arroyo is a new kind of stream processing engine, built from the ground up to make real-time easier than batch. Arroyo was designed from the start so that anyone with SQL experience can build reliable, efficient, and correct streaming pipelines. Data scientists and engineers can build end-to-end real-time applications, models, and dashboards, without a separate team of streaming experts. Transform, filter, aggregate, and join data streams by writing SQL, with sub-second results. Your streaming pipelines shouldn't page someone just because Kubernetes decided to reschedule your pods. Arroyo is built to run in modern, elastic cloud environments, from simple container runtimes like Fargate to large, distributed deployments on the Kubernetes logo Kubernetes.

About

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Individuals in search of a tool to transform, filter, aggregate, and join data streams

Audience

Real-Time Data Streaming solution for businesses

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Arroyo
United States
www.arroyo.dev/

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org/streaming/

Alternatives

Alternatives

ksqlDB

ksqlDB

Confluent
Samza

Samza

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation

Categories

Categories

Integrations

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

Integrations

AWS Fargate
Amazon Kinesis
Apache Avro
Apache Flink
Apache Kafka
Apache Parquet
Apache Spark
Confluent
Delta Lake
Docker
JSON
Kubernetes
PostgreSQL
PubSub+ Platform
Python
Redis
Rust
SQL
Claim Arroyo and update features and information
Claim Arroyo and update features and information
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Claim Spark Streaming and update features and information