Apache Spark Streaming Reviews

Name: Apache Spark Streaming
Brand: Apache
Rating: 4.0 (11 reviews)

4.0 out of 5

11 reviews
91% willing to recommend

What is Apache Spark Streaming?

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

Get the Streaming Analytics Buyer's Guide and find out what your peers are saying about Apache Spark Streaming, Databricks, Confluent and more!

Apache Spark Streaming is the #10 ranked solution in Streaming Analytics tools. PeerSpot users give Apache Spark Streaming an average rating of 8.0 out of 10. Based on the analysis of the 11 most recent Apache Spark Streaming reviews, the overall sentiment is positive, with a sentiment score of 7.4. (Among the highest in the category). Apache Spark Streaming is most commonly compared to Databricks: Apache Spark Streaming vs Databricks. Apache Spark Streaming is popular among the large enterprise segment, accounting for 64% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 24% of all views.

Buyer's Guide

Streaming Analytics

December 2024

Get the category report

Helped 824,067 peers since 2012

Featured reviews

Oscar Estorach

Chief Data-strategist and Director at Theworkshop.es

What I like about Spark is its versatility in supporting multiple languages and that makes it my preferred choice for building scalable and efficient systems, whether it is hooking databases with web applications or handling large-scale data transformations. Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows. It works well in the cloud, and you can structure data using Databricks or Spark, providing flexibility for different projects. Spark Streaming's flexibility shines when dealing with large-scale data streams. It caters to different needs, offering real-time insights for tasks like online sales analytics. The ability to prioritize data streams is valuable, especially for monitoring competitor prices online.

Read full review

AbhishekGupta

Engineering Leader at Walmart

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. Apache Spark Streaming does not have auto-tuning. A customer needs to invest a lot, in terms of management and maintenance.

Read full review

Prashast Tripathi

Data Engineer at DTDL

I rate the initial setup a five on a scale from one to ten, where one is difficult, and ten is easy. Apache Spark Streaming's deployment usually takes two to three minutes. The solution deployment is a fully automated process, and we have a CI/CD process in place, so we trigger Jenkins Pipeline for the deployment. The solution is deployed on a hybrid cloud. The deployment can be done with just one click, so not even a person is needed for deployment.

Read full review

Apache Spark Streaming mindshare

As of December 2024, the mindshare of Apache Spark Streaming in the Streaming Analytics category stands at 3.6%, down from 4.6% compared to the previous year, according to calculations based on PeerSpot user engagement data.

Streaming Analytics

Key learnings from peers

Last updated Dec 18, 2024

Valuable Features

"Spark Streaming is critical, quite stable, full-featured, and scalable."
"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."
"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."

Room for Improvement

"We don't have enough experience to be judgmental about its flaws."
"The debugging aspect could use some improvement."
"Integrating event-level streaming capabilities could be beneficial."

ROI

Pricing

Apache Spark Streaming is generally considered affordable, particularly due to its open-source nature, resulting in minimal or no licensing costs. Users find cloud deployment less expensive than on-premises solutions. Many utilize the community version for cost-effectiveness, acknowledging that while affordable, acquiring commercial versions or support services may incur additional costs. The product is well-rated for pricing, with some users indicating it ranks high on affordability compared to other enterprise solutions.

"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."

Popular Use Cases

Service and Support

Apache Spark Streaming offers strong community support and comprehensive documentation. Users often rely on external consulting and publicly available resources rather than directly contacting Apache support. The open-source community is beneficial, with sufficient assistance available when needed. Organizations typically depend on readily accessible information without requiring Apache's direct aid.