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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

reviewer1516182 - PeerSpot reviewer
Chief Innovation & Technology Leader at a mining and metals company with 1,001-5,000 employees
Mar 19, 2021
The solution is better than average and some of the valuable features include efficiency and stability.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at Theworkshop.es
Aug 18, 2021
The solution is very stable and reliable.
reviewer1494531 - PeerSpot reviewer
Head of Data Science at a energy/utilities company with 10,001+ employees
Apr 11, 2022
As an open-source solution, using it is basically free.
Learn what your peers think about Apache Spark Streaming. Get advice and tips from experienced pros sharing their opinions. Updated: December 2025.
879,422 professionals have used our research since 2012.
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.
SB
Sr Technical Analyst at Sumtotal
Nov 21, 2022
It's the fastest solution on the market with low latency data on data transformations.
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.
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.
reviewer2392494 - PeerSpot reviewer
Enterprise Data Architect at a pharma/biotech company with 11-50 employees
Apr 19, 2024
The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams.
RK
DevOps engineer at Vvolve management consultants
Jun 3, 2024
Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way.
 

Apache Spark Streaming Cons review quotes

reviewer1516182 - PeerSpot reviewer
Chief Innovation & Technology Leader at a mining and metals company with 1,001-5,000 employees
Mar 19, 2021
There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at Theworkshop.es
Aug 18, 2021
The solution itself could be easier to use.
reviewer1494531 - PeerSpot reviewer
Head of Data Science at a energy/utilities company with 10,001+ employees
Apr 11, 2022
We would like to have the ability to do arbitrary stateful functions in Python.
Learn what your peers think about Apache Spark Streaming. Get advice and tips from experienced pros sharing their opinions. Updated: December 2025.
879,422 professionals have used our research since 2012.
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.
SB
Sr Technical Analyst at Sumtotal
Nov 21, 2022
The initial setup is quite complex.
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.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at Theworkshop.es
Jan 25, 2024
In terms of improvement, the UI could be better.
reviewer2392494 - PeerSpot reviewer
Enterprise Data Architect at a pharma/biotech company with 11-50 employees
Apr 19, 2024
Integrating event-level streaming capabilities could be beneficial.
RK
DevOps engineer at Vvolve management consultants
Jun 3, 2024
The debugging aspect could use some improvement.