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Apache Spark Streaming pros and cons

Vendor: Apache
3.9 out of 5

Pros & Cons summary

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Prominent pros & cons

PROS

Apache Spark Streaming offers strong capabilities for near real-time analytics and allows developers to build APIs for code-streaming pipelines.
It is known for being the fastest on the market with low latency for data transformation and offers significant stability and scalability.
Apache Spark Streaming's integration with Anaconda and Miniconda enhances its machine learning capabilities and enables database interaction through data frames or data sets.
The platform supports various windowing options such as tumbling, sliding, or static windows, offering flexibility in data processing.
The benefits of using Apache Spark Streaming include cost savings, time savings, and efficiency improvements in data storage and handling.

CONS

Apache Spark Streaming's configuration section is too developer-focused and could be more business user-friendly.
Memory management and latency issues exist, making it unsuitable for real-time analytics or IoT use cases.
Real-time processing is needed instead of the current micro-batch or near real-time capability.
Integrating event-level streaming capabilities could improve its functionality.
Monitoring can be challenging due to the large and often meaningless logs generated by streaming applications.
 

Apache Spark Streaming Pros review quotes

Himansu Jena - PeerSpot reviewer
Sr Project Manager at Raj Subhatech
Aug 19, 2025
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.
Kuldeep Pal - PeerSpot reviewer
Data Engineer at Walmart Global Tech
Aug 22, 2025
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.
Khoa Dang Le - PeerSpot reviewer
Principal AI Engineer at IMT Solutions
Sep 26, 2025
The main benefits of Apache Spark Streaming include cost savings, time savings, and efficiency improvements about data storage.
Learn what your peers think about Apache Spark Streaming. Get advice and tips from experienced pros sharing their opinions. Updated: May 2026.
893,221 professionals have used our research since 2012.
Shahzad Munir - PeerSpot reviewer
Sr. Manager Data Engineer at a tech consulting company with 51-200 employees
Aug 25, 2025
I appreciate Apache Spark Streaming's micro-batching capabilities; the watermarking functionality and related features are quite good.
Venkata Phaneendra Reddy Janga - PeerSpot reviewer
Data Engineer III at a tech consulting company with 10,001+ employees
Aug 18, 2025
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.
Ajay Hiremath - PeerSpot reviewer
Gen AI Lead/Architect at Alvaria
Sep 9, 2025
For Apache Spark Streaming, the feature I appreciated most is that it provides live data delivery; additionally, it provides the capability to send a larger amount of data in parallel.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at Theworkshop.es
Jan 25, 2024
Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.
AbhishekGupta - PeerSpot reviewer
Engineering Leader at Walmart
Oct 8, 2022
Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services.
DR
Chief Technology Officer at Teslon Technologies Pvt Ltd
Jun 8, 2023
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.
Prashast Tripathi - PeerSpot reviewer
Data Engineer at a comms service provider with 201-500 employees
Jul 24, 2023
Apache Spark Streaming has features like checkpointing and Streaming API that are useful.
 

Apache Spark Streaming Cons review quotes

Himansu Jena - PeerSpot reviewer
Sr Project Manager at Raj Subhatech
Aug 19, 2025
When dealing with various data types including COBOL, Excel, JSON, video, audio, and MPG files, challenges can arise with incomplete or missing values.
Kuldeep Pal - PeerSpot reviewer
Data Engineer at Walmart Global Tech
Aug 22, 2025
While it is reliable, there are some issues with Apache Spark Streaming as it is not 100% reliable.
Khoa Dang Le - PeerSpot reviewer
Principal AI Engineer at IMT Solutions
Sep 26, 2025
The problem is we need to use it in a certain manner. After that, we need to apply another pipeline for the machine learning processes, and that's what we work on.
Learn what your peers think about Apache Spark Streaming. Get advice and tips from experienced pros sharing their opinions. Updated: May 2026.
893,221 professionals have used our research since 2012.
Shahzad Munir - PeerSpot reviewer
Sr. Manager Data Engineer at a tech consulting company with 51-200 employees
Aug 25, 2025
Monitoring is an area where they could definitely improve Apache Spark Streaming. When you have a streaming application, it generates numerous logs. After some time, the logs become meaningless because they're quite large and impossible to open.
Venkata Phaneendra Reddy Janga - PeerSpot reviewer
Data Engineer III at a tech consulting company with 10,001+ employees
Aug 18, 2025
One improvement I would expect is real-time processing instead of micro-batch or near real-time.
Ajay Hiremath - PeerSpot reviewer
Gen AI Lead/Architect at Alvaria
Sep 9, 2025
The downside is when you have this the other way around in the columns, it becomes really hard to use.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at Theworkshop.es
Jan 25, 2024
In terms of improvement, the UI could be better.
AbhishekGupta - PeerSpot reviewer
Engineering Leader at Walmart
Oct 8, 2022
The service structure of Apache Spark Streaming can improve. There are a lot of issues with memory management and latency. There is no real-time analytics. We recommend it for the use cases where there is a five-second latency, but not for a millisecond, an IOT-based, or the detection anomaly-based. Flink as a service is much better.
DR
Chief Technology Officer at Teslon Technologies Pvt Ltd
Jun 8, 2023
It was resource-intensive, even for small-scale applications.
Prashast Tripathi - PeerSpot reviewer
Data Engineer at a comms service provider with 201-500 employees
Jul 24, 2023
The cost and load-related optimizations are areas where the tool lacks and needs improvement.