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Spark Streaming VS Leo Platform

Compare Spark Streaming VS Leo Platform and see what are their differences

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Spark Streaming logo Spark Streaming

Spark Streaming makes it easy to build scalable and fault-tolerant streaming applications.

Leo Platform logo Leo Platform

Leo enables teams to innovate faster by providing visibility and control for data streams.
  • Spark Streaming Landing page
    Landing page //
    2022-01-10
  • Leo Platform Landing page
    Landing page //
    2021-10-19

Spark Streaming

Categories
  • Big Data
  • Stream Processing
  • Data Management
  • Analytics
Website spark.apache.org
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Leo Platform

Categories
  • Big Data
  • Stream Processing
  • Data Management
  • Analytics
Website leoplatform.io
Edit details

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

Leo Platform videos

No Leo Platform videos yet. You could help us improve this page by suggesting one.

+ Add video

Category Popularity

0-100% (relative to Spark Streaming and Leo Platform)

Spark Streaming

Leo Platform

Stream Processing
67 67%
Stream Processing
33% 33
Data Management
69 69%
Data Management
31% 31
Big Data
71 71%
Big Data
29% 29
Analytics
58 58%
Analytics
42% 42

User comments

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Social recommendations and mentions

Based on our record, Spark Streaming seems to be more popular. 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.

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

Leo Platform mentions (0)

We have not tracked any mentions of Leo Platform yet. Tracking of Leo Platform recommendations started around Mar 2021.

What are some alternatives?

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

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

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

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

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

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

OpenZoo - OpenZoo is an open-source, distributed, stream and batch processing framework.

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