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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Apache Flink serves as a powerful framework and distributed processing engine tailored for executing stateful computations on both unbounded and bounded data streams. It has been engineered to operate seamlessly across various cluster environments, delivering computations with impressive in-memory speed and scalability. Data of all types is generated as a continuous stream of events, encompassing credit card transactions, sensor data, machine logs, and user actions on websites or mobile apps. The capabilities of Apache Flink shine particularly when handling both unbounded and bounded data sets. Its precise management of time and state allows Flink’s runtime to support a wide range of applications operating on unbounded streams. For bounded streams, Flink employs specialized algorithms and data structures optimized for fixed-size data sets, ensuring remarkable performance. Furthermore, Flink is adept at integrating with all previously mentioned resource managers, enhancing its versatility in various computing environments. This makes Flink a valuable tool for developers seeking efficient and reliable stream processing solutions.

Description

Spark Streaming extends the capabilities of Apache Spark by integrating its language-based API for stream processing, allowing you to create streaming applications in the same manner as batch applications. This powerful tool is compatible with Java, Scala, and Python. One of its key features is the automatic recovery of lost work and operator state, such as sliding windows, without requiring additional code from the user. By leveraging the Spark framework, Spark Streaming enables the reuse of the same code for batch processes, facilitates the joining of streams with historical data, and supports ad-hoc queries on the stream's state. This makes it possible to develop robust interactive applications rather than merely focusing on analytics. Spark Streaming is an integral component of Apache Spark, benefiting from regular testing and updates with each new release of Spark. Users can deploy Spark Streaming in various environments, including Spark's standalone cluster mode and other compatible cluster resource managers, and it even offers a local mode for development purposes. For production environments, Spark Streaming ensures high availability by utilizing ZooKeeper and HDFS, providing a reliable framework for real-time data processing. This combination of features makes Spark Streaming an essential tool for developers looking to harness the power of real-time analytics efficiently.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Iceberg Yes 
Apache Knox Yes 
Apache Kudu Yes 
Arroyo Yes 
Deep.BI Yes 
DeltaStream Yes 
E-MapReduce Yes 
Foundational Yes 
Gable Yes 
GlassFlow Yes 
Hue Yes 
Netdata Yes 
PubSub+ Platform No 
Redpanda Agentic Data Plane Yes 
ScaleOps Yes 
Scalytics Connect Yes 
Streamkap Yes 
Ververica Yes 
Warp 10 Yes 
lakeFS Yes 

Integrations

Apache Iceberg No 
Apache Knox No 
Apache Kudu No 
Arroyo No 
Deep.BI No 
DeltaStream No 
E-MapReduce No 
Foundational No 
Gable No 
GlassFlow No 
Hue No 
Netdata No 
PubSub+ Platform Yes 
Redpanda Agentic Data Plane No 
ScaleOps No 
Scalytics Connect No 
Streamkap No 
Ververica No 
Warp 10 No 
lakeFS No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

flink.apache.org

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org/streaming/

Product Features

Streaming Analytics

Data Enrichment No 
Data Wrangling / Data Prep No 
Multiple Data Source Support No 
Process Automation No 
Real-time Analysis / Reporting No 
Visualization Dashboards No 

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