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Goka VS Spark Streaming

Compare Goka VS Spark Streaming and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Goka logo Goka

Goka is a distributed stream processing library for Apache Kafka written in Go.

Spark Streaming logo Spark Streaming

Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.
  • Goka Landing page
    Landing page //
    2023-09-18
  • Spark Streaming Landing page
    Landing page //
    2022-01-10

Goka videos

+ Add

2008 BMS GOKA 800cc

More videos:

  • Review - GOKA CATTLE FEED
  • Review - Best medicine for healing cracks | goka jalwatawar malam | review | usage | indication | content

Spark Streaming videos

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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 Goka and Spark Streaming)

Goka

Spark Streaming

Stream Processing
18 18%
Stream Processing
82% 82
Databases
100 100%
Databases
0% 0
Big Data
21 21%
Big Data
79% 79
Data Management
0 0%
Data Management
100% 100

User comments

Share your experience with using Goka 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 Goka. 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.

Goka mentions (1)

  • Go and Kafka
    You might want to try: https://github.com/lovoo/goka -- it uses levelDB to keep state from a stream. The application we wrote in-house with goka can process (keeping state) approximately 800+ messages/sec per consumer in a consumer-group. Source: about 3 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 / 3 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 Goka and Spark Streaming, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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

Tigon - Tigon is an open source real-time stream processing framework built on top of Apache Hadoop and Apache HBase.

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

Lightbend Akka Platform - Lightbend Fast Data Platform is the easy on-ramp to successful streaming Fast Data applications.

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

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