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Apache Spark Streaming vs Confluent comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Apache Spark Streaming
Ranking in Streaming Analytics
10th
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
17
Ranking in other categories
No ranking in other categories
Confluent
Ranking in Streaming Analytics
6th
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
25
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of May 2026, in the Streaming Analytics category, the mindshare of Apache Spark Streaming is 4.4%, up from 2.6% compared to the previous year. The mindshare of Confluent is 6.6%, down from 8.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Confluent6.6%
Apache Spark Streaming4.4%
Other89.0%
Streaming Analytics
 

Featured Reviews

Himansu Jena - PeerSpot reviewer
Sr Project Manager at Raj Subhatech
Efficient real-time data management and analysis with advanced features
There are various ways we can improve Apache Spark Streaming through best practices. The initial part requires attention to batch interval tuning, which helps small intervals in micro batches based on latency requirements and helps prevent back pressure. We can use data formats such as Parquet or ORC for storage that needs faster reads and leveraging feature predicate push-down optimizations. We can implement serialization which helps with any Kyro in terms of .NET or Java. We have boxing and unboxing serialization for XML and JSON for converting key-pair values stored in browser. We can also implement caching mechanisms for storing and recomputing multiple operations. We can use specified joins which help with smaller databases, and distributed joins can minimize users. We can implement project optimization memory for CPU efficiency, known as Tungsten. Additionally, load balancing, checkpointing, and schema evaluation are areas to consider based on performance and bottlenecks. We can use Bugzilla tools for tracking and Splunk to monitor the performance of process systems, utilization, and performance based on data frames or data sets.
PavanManepalli - PeerSpot reviewer
AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo
Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing
I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"With Apache Spark Streaming, you can have multiple kinds of windows; depending on your use case, you can select either a tumbling window, a sliding window, or a static window to determine how much data you want to process at a single point of time."
"With Apache Spark Streaming's integration with Anaconda and Miniconda with Python, I interact with databases using data frames or data sets in micro versions and create solutions based on business expectations for decision-making, logistic regression, linear regression, or machine learning which provides image or voice record and graphical data for improved accuracy."
"The solution is better than average and some of the valuable features include efficiency and stability."
"The main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage."
"By integrating Apache Spark Streaming, the data freshness rate, and latency have significantly improved from 24-hour batch processing to less than one minute, facilitating faster communication to downstream systems, aiding marketing campaigns."
"Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."
"The solution is better than average and some of the valuable features include efficiency and stability."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"It is also good for knowledge base management."
"The most valuable feature of Confluent is the wide range of features provided; they're leading the market in this category."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"Confluent is an amazing tool that is highly configurable, integrates very well with Jira, and lets you create nice documentation for various products while also supporting reporting and online content hosting."
"I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
 

Cons

"The solution itself could be easier to use."
"One improvement I would expect is real-time processing instead of micro-batch or near real-time."
"The downside is when you have this the other way around in the columns, it becomes really hard to use."
"The debugging aspect could use some improvement."
"In terms of improvement, the UI could be better."
"Integrating event-level streaming capabilities could be beneficial."
"When dealing with various data types including COBOL, Excel, JSON, video, audio, and MPG files, challenges can arise with incomplete or missing values."
"The initial setup is quite complex."
"The pricing was high for our needs. We should not have to pay for features we do not use."
"There is a limitation when it comes to seamlessly importing Microsoft documents into Confluent pages, which can be inconvenient for users who frequently work with Microsoft Office tools and need to transition their content to Confluent."
"It could have more integration with different platforms."
"From the control center perspective, there is a lot of room for improvement in the visualization."
"Confluent has a good monitoring tool, but it's not customizable."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
 

Pricing and Cost Advice

"Spark is an affordable solution, especially considering its open-source nature."
"On a scale from one to ten, where one is expensive, or not cost-effective, and ten is cheap, I rate the price a seven."
"I was using the open-source community version, which was self-hosted."
"People pay for Apache Spark Streaming as a service."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."
"Confluent is an expensive solution."
"The solution is cheaper than other products."
"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"It comes with a high cost."
"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."
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Top Industries

By visitors reading reviews
Financial Services Firm
22%
Comms Service Provider
9%
Computer Software Company
8%
Marketing Services Firm
7%
Financial Services Firm
15%
Retailer
10%
Computer Software Company
10%
Manufacturing Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise2
Large Enterprise7
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise4
Large Enterprise16
 

Questions from the Community

What needs improvement with Apache Spark Streaming?
One of the improvements we need is in Spark SQL and the machine learning library. I don't think there is too much to work on, but the issue is when we want to use machine learning, we always need t...
What is your primary use case for Apache Spark Streaming?
We work with Apache Spark Streaming for our project because we use that as one of the landing data sources, and we work with it to ensure we can get all of the data before it goes through our data ...
What advice do you have for others considering Apache Spark Streaming?
One thing I would share with other organizations considering Apache Spark Streaming is the necessity of having effective data storage. We want to ensure we acquire and manage our data storage effec...
What is your experience regarding pricing and costs for Confluent?
They charge a lot for scaling, which makes it expensive.
What needs improvement with Confluent?
I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about ...
What is your primary use case for Confluent?
The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...
 

Also Known As

Spark Streaming
No data available
 

Overview

 

Sample Customers

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Find out what your peers are saying about Apache Spark Streaming vs. Confluent and other solutions. Updated: April 2026.
893,164 professionals have used our research since 2012.