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Confluent VS IBM Cloud Pak for Data

Compare Confluent 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

Confluent logo Confluent

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

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.
  • Confluent Landing page
    Landing page //
    2023-10-22
  • IBM Cloud Pak for Data Landing page
    Landing page //
    2023-02-11

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?😩

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 Confluent and IBM Cloud Pak for Data)

Confluent

IBM Cloud Pak for Data

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

User comments

Share your experience with using Confluent 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 Confluent and IBM Cloud Pak for Data

Confluent Reviews

We have no reviews of Confluent 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, Confluent seems to be more popular. It has been mentiond 1 time 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

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 Confluent and IBM Cloud Pak for Data, 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.

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.

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

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

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

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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