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Spark Streaming VS IBM Cloud Pak for Data

Compare Spark Streaming VS IBM Cloud Pak for Data and see what are their differences

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

Spark Streaming logo Spark Streaming

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

IBM Cloud Pak for Data logo IBM Cloud Pak for Data

Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.
  • Spark Streaming Landing page
    Landing page //
    2022-01-10
  • IBM Cloud Pak for Data Landing page
    Landing page //
    2023-02-11

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

IBM Cloud Pak for Data videos

+ Add

IBM Cloud Pak for Data - Product Walkthrough

More videos:

  • Review - Overview of IBM Cloud Pak for Data

Category Popularity

0-100% (relative to Spark Streaming and IBM Cloud Pak for Data)

Spark Streaming

IBM Cloud Pak for Data

Stream Processing
100 100%
Stream Processing
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Data Management
100 100%
Data Management
0% 0
Data Integration
0 0%
Data Integration
100% 100

User comments

Share your experience with using Spark Streaming and IBM Cloud Pak for Data. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Spark Streaming and IBM Cloud Pak for Data

Spark Streaming Reviews

We have no reviews of Spark Streaming yet.
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IBM Cloud Pak for Data Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
IBM Cloud Pak for Data is a fully-integrated, cloud native, data and AI platform designed for sophisticated DataOps and business analytics solutions. IBM boasts a potential for a 25-65% reduction in extract, transform, load (ETL) requests by eliminating the complexities of data integration of different data types and structures using Cloud Pak for Data. You can customize...
Source: theqalead.com

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 / 4 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

IBM Cloud Pak for Data mentions (0)

We have not tracked any mentions of IBM Cloud Pak for Data yet. Tracking of IBM Cloud Pak for Data recommendations started around Mar 2021.

What are some alternatives?

When comparing Spark Streaming and IBM Cloud Pak for Data, you can also consider the following products

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

Denodo - Denodo delivers on-demand real-time data access to many sources as integrated data services with high performance using intelligent real-time query optimization, caching, in-memory and hybrid strategies.

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

Azure Databricks - Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.

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

data.world - The social network for data people

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