Apache NiFi vs IBM Streams comparison

The compared Apache and IBM solutions aren't in the same category. Apache is ranked #8 in CS , with an average rating of 7.6, and holds a 7.9% mindshare in the category. IBM is ranked #18 in SA , with an average rating of 7.0, and holds a 0.8% mindshare. Additionally, 90% of Apache users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Apache NiFi

Read 11 Apache NiFi reviews

2,418 Views
1,132 Comparison Views

90% willing to recommend

IBM Streams

Read 5 IBM Streams reviews

503 Views
415 Comparison Views

100% willing to recommend

Apache NiFi

IBM Streams

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Apache NiFi and IBM Streams based on real PeerSpot user reviews.

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Buyer's Guide

Compute Service

December 2024

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Categories and Ranking

Apache NiFi

Average Rating

7.8

Number of Reviews

Ranking in other categories

Compute Service (8th)

IBM Streams

Average Rating

8.2

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Streaming Analytics (18th)

Mindshare comparison

Apache NiFi and IBM Streams aren’t in the same category and serve different purposes. Apache NiFi is designed for Compute Service and holds a mindshare of 7.9%, up 6.0% compared to last year.
IBM Streams, on the other hand, focuses on Streaming Analytics, holds 0.8% mindshare, down 1.0% since last year.

Compute Service

Streaming Analytics

Featured Reviews

Bruno_Silva

Partner at Timestamp, SA

Very easy to schedule jobs that realize improvements and monetize

The use case templates could be more precise to typical business needs. Available templates and model workflows are very high-level so don't really match real needs. It would help to have templates that allow us to see business opportunities. It would help to be able to copy workflow to another device rather than having to ingest it.

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Ahmed_Emad

Territory Sales Leader at Sumerge

A solution for data pipelines but has connector limitations

We have used Kafka for seven years. IBM streams gives you many OOTB features that can boost the time-to-market, especially when it comes to reporting and monitoring for example. Confluent is recognized as one of the leaders in this space and the main reason for this is related to the complete vision of the platform also the large number of connectors. This gives the edge and competitive advatnage.

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

15%

Manufacturing Company

Retailer

Financial Services Firm

32%

Computer Software Company

20%

Healthcare Company

Retailer

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Apache NiFi?

The initial setup is very easy.

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What is your experience regarding pricing and costs for Apache NiFi?

I used the tool's free version.

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What needs improvement with Apache NiFi?

The tool should incorporate more tutorials for advanced use cases. It has tutorials for simple use cases.

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What is your experience regarding pricing and costs for IBM Streams?

The solution’s licenses pricing is different from one region to another region. I rate the solution’s pricing a seven out of ten.

See all answers

What needs improvement with IBM Streams?

the limited number of connectors. This shall be overcome with work-arounds or eventually buying additional connectors to complete the solution.

See all answers

What is your primary use case for IBM Streams?

We use the solution for data pipeline by modernizing the traditional ETL jobs done through advanced streaming. Another use case is building the g2g streaming platform, which facilitates data exchan...

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Comparisons

Google Cloud Dataflow vs Apache NiFi

Compared 30% of the time

AWS Lambda vs Apache NiFi

Compared 25% of the time

Apache Spark vs Apache NiFi

Compared 13% of the time

Azure Stream Analytics vs Apache NiFi

Compared 8% of the time

AWS Batch vs Apache NiFi

Compared 3% of the time

More Apache NiFi Competitors

Confluent vs IBM Streams

Compared 44% of the time

Apache Flink vs IBM Streams

Compared 22% of the time

Amazon MSK vs IBM Streams

Compared 19% of the time

More IBM Streams Competitors

Product Reports

Buyer's Guide

Apache NiFi

December 2024

Download Apache NiFi product report

Buyer's Guide

Streaming Analytics

December 2024

Download IBM Streams product report

Also Known As

No data available

IBM InfoSphere Streams

Learn More

Apache

IBM

Overview

Apache NiFi is an easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

IBM Streams is an advanced analytic platform that allows user-developed applications to quickly ingest, analyze and correlate information as it arrives from thousands of data stream sources. The solution can handle very high data throughput rates, up to millions of events or messages per second. Streams helps you analyze data in motion, simplify development of streaming applications, and extend the value of existing systems.

Sample Customers

Macquarie Telecom Group, Dovestech, Slovak Telekom, Looker, Hastings Group

Globo TV, All England Lawn Tennis Club, CenterPoint Energy, Consolidated Communications Holdings, Darwin Ecosystem, Emory University Hospital, ICICI Securities, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Living Roads, Mobileum, Optibus, Southern Ontario Smart Computing Innovation Platform (SOSCIP), University of Alberta, University of Montana, University of Ontario Institute of Technology, Wimbledon 2015

Find out what your peers are saying about Amazon Web Services (AWS), Apache, Spot by NetApp and others in Compute Service. Updated: December 2024.

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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.