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Confluent VS Spark Streaming

Compare Confluent VS Spark Streaming and see what are their differences

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Confluent logo Confluent

Confluent offers a real-time data platform built around Apache Kafka.

Spark Streaming logo Spark Streaming

Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.
  • Confluent Landing page
    Landing page //
    2023-10-22
  • Spark Streaming Landing page
    Landing page //
    2022-01-10

Confluent

Categories
  • Big Data
  • Stream Processing
  • Data Management
  • Analytics
Website confluent.io
Pricing URL Official Confluent Pricing
Details $
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Spark Streaming

Categories
  • Big Data
  • Stream Processing
  • Data Management
  • Analytics
Website spark.apache.org
Pricing URL-
Details $-
Edit details

Confluent videos

+ Add

1. Intro | Monitoring Kafka in Confluent Control Center

More videos:

  • Review - Jason Gustafson, Confluent: Revisiting Exactly One Semantics (EOS) | Bay Area Apache Kafka® Meetup
  • Review - CLEARER SKIN AFTER 1 USE‼️| Ancient Cosmetics Update✨| CONFLUENT & RETICULATED PAPILLOMATOSIS CURE?😩

Spark Streaming videos

+ Add

Spark Streaming Vs Kafka Streams || Which is The Best for Stream Processing?

More videos:

  • Tutorial - Spark Streaming Vs Structured Streaming Comparison | Big Data Hadoop Tutorial

Category Popularity

0-100% (relative to Confluent and Spark Streaming)

Confluent

Spark Streaming

Stream Processing
59 59%
Stream Processing
41% 41
Big Data
61 61%
Big Data
39% 39
Data Management
53 53%
Data Management
47% 47
Analytics
57 57%
Analytics
43% 43

User comments

Share your experience with using Confluent and Spark Streaming. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Spark Streaming should be more popular than Confluent. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Confluent mentions (1)

  • Spring Boot Event Streaming with Kafka
    We’re going to setup a Kafka cluster using confluent.io, create a producer and consumer as well as enhance our behavior driven tests to include the new interface. We’re going to update our helm chart so that the updates are seamless to Kubernetes and we’re going to leverage our observability stack to propagate the traces in the published messages. Source: about 2 years ago

Spark Streaming mentions (3)

  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 2 months ago
  • Machine Learning Pipelines with Spark: Introductory Guide (Part 1)
    Spark Streaming: The component for real-time data processing and analytics. - Source: dev.to / over 1 year ago
  • Spark for beginners - and you
    Is a big data framework and currently one of the most popular tools for big data analytics. It contains libraries for data analysis, machine learning, graph analysis and streaming live data. In general Spark is faster than Hadoop, as it does not write intermediate results to disk. It is not a data storage system. We can use Spark on top of HDFS or read data from other sources like Amazon S3. It is the designed... - Source: dev.to / over 2 years ago

What are some alternatives?

When comparing Confluent and Spark Streaming, you can also consider the following products

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Azure Stream Analytics - Azure Stream Analytics offers real-time stream processing in the cloud.

Striim - Striim provides an end-to-end, real-time data integration and streaming analytics platform.

PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time

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