Apache Spark Streaming vs Upsolver comparison

Apache and Upsolver are both solutions in the Streaming Analytics category. Apache is ranked #10 with an average rating of 8.2, while Upsolver is ranked #17 with an average rating of 8.5. Apache holds a 2.6% mindshare in SA, compared to Upsolver’s 0.3% mindshare. Additionally, 91% of Apache users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Apache Spark Streaming

Read 11 Apache Spark Streaming reviews

1,578 Views
1,126 Comparison Views

91% willing to recommend

Upsolver

Read 2 Upsolver reviews

104 Views
69 Comparison Views

100% willing to recommend

Apache Spark Streaming

Upsolver

Comparison Buyer's Guide

Download the report

Executive Summary

We performed a comparison between Apache Spark Streaming and Upsolver based on real PeerSpot user reviews.

Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Apache Spark Streaming vs. Upsolver Report (Updated: April 2025).

Buyer's Guide

Apache Spark Streaming vs. Upsolver

April 2025

Download the complete report

Helped 851,371 peers since 2012

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

8.0

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Upsolver

Ranking in Streaming Analytics

17th

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Integration (38th)

Mindshare comparison

As of May 2025, in the Streaming Analytics category, the mindshare of Apache Spark Streaming is 2.6%, down from 3.8% compared to the previous year. The mindshare of Upsolver is 0.3%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

AbhishekGupta

Engineering Leader at Walmart

Easy integration, beneficial auto-scaling, and good open-sourced support community

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

Snehasish Das

Technology Leader at eTCaaS

Allows for data to be moved across platforms and different data technologies

The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies. Upsolver does this in a quick time, unlike traditional processes which are time-consuming. Additionally, it offers scalability for large volumes of data, with performance and ease of cloud-native integration.

Read full review

Quotes from Members

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

Pros

"It's the fastest solution on the market with low latency data on 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."

"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."

"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."

"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."

"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."

"The solution is very stable and reliable."

"The solution is better than average and some of the valuable features include efficiency and stability."

More Apache Spark Streaming pros

"Customer service is excellent, and I would rate it between eight point five to nine out of ten."

"The most prominent feature of Upsolver is its function as an ETL tool, allowing data to be moved across platforms and different data technologies."

"It was easy to use and set up, with a nearly no-code interface that relied mostly on drag-and-drop functionality."

Cons

"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."

"We don't have enough experience to be judgmental about its flaws."

"The cost and load-related optimizations are areas where the tool lacks and needs improvement."

"The solution itself could be easier to use."

"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."

"In terms of improvement, the UI could be better."

"Integrating event-level streaming capabilities could be beneficial."

"It was resource-intensive, even for small-scale applications."

More Apache Spark Streaming cons

"There is room for improvement in query tuning."

"On the stability side, I would rate it seven out of ten. Using multiple cloud providers and data engineering technologies creates complexity, and managing different plugins is not always easy, but they are working on it."

"Upsolver excels in ETL and data aggregation, while ThoughtSpot is strong in natural language processing for querying datasets. Combining these tools can be very effective: Upsolver handles aggregation and ETL, and ThoughtSpot allows for natural language queries. There’s potential for highlighting these integrations in the future."

Pricing and Cost Advice

"Spark is an affordable solution, especially considering its open-source nature."

"I was using the open-source community version, which was self-hosted."

"People pay for Apache Spark Streaming as a service."

"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."

"Upsolver is affordable at approximately $225 per terabyte per year."

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

851,371 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

29%

Computer Software Company

21%

Manufacturing Company

University

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Apache Spark Streaming?

Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.

See all answers

What needs improvement with Apache Spark Streaming?

We don't have enough experience to be judgmental about its flaws, as we've only used stable features like batch micro-batch. Integration poses no problem; however, I don't use some features and can...

See all answers

What is your primary use case for Apache Spark Streaming?

We use Spark Streaming in a micro-batch region. It's not a full real-time system, but it offers high performance and low latency.

See all answers

What is your experience regarding pricing and costs for Upsolver?

Upsolver is affordable at approximately $225 per terabyte per year. Compared to what I know from others, it's cheaper than many other products.

See all answers

What needs improvement with Upsolver?

There is room for improvement in query tuning. Upsolver could do a more in-depth analysis in employing machine power, such as CPU and memory, to enhance query performance. Furthermore, allocating C...

See all answers

What is your primary use case for Upsolver?

I am working as a consultant and currently have my own consultancy services. I provide services to companies that are data-heavy and looking for data engineering solutions for their business needs....

See all answers

Comparisons

Spring Cloud Data Flow vs Apache Spark Streaming

Compared 21% of the time

Apache Pulsar vs Apache Spark Streaming

Compared 20% of the time

Azure Stream Analytics vs Apache Spark Streaming

Compared 13% of the time

Amazon Kinesis vs Apache Spark Streaming

Compared 13% of the time

Apache Flink vs Apache Spark Streaming

Compared 10% of the time

More Apache Spark Streaming Competitors

Databricks vs Upsolver

Compared 100% of the time

More Upsolver Competitors

Product Reports

Buyer's Guide

Streaming Analytics

May 2025

Download Apache Spark Streaming product report

Buyer's Guide

Data Integration

May 2025

Download Upsolver product report

Also Known As

Spark Streaming

No data available

Overview

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

Apache

Upsolver's mission is to turn engineering-intensive data lakes into easy-to-use repositories that serve 50X more data professionals compared to the status-quo today. Upsolver cuts 95% from the tedious process of preparing event data for analytics and machine learning, using a visual SQL-based interface, a cloud-native data platform and deep technology for stream-processing, indexing and eventually-consistent file systems.

Upsolver

Sample Customers

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.

Information Not Available

Buyer's Guide

Apache Spark Streaming vs. Upsolver

April 2025

Free Report: Apache Spark Streaming vs. Upsolver

Find out what your peers are saying about Apache Spark Streaming vs. Upsolver and other solutions. Updated: April 2025.

DOWNLOAD NOW

851,371 professionals have used our research since 2012.

See our Apache Spark Streaming vs. Upsolver report.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics 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.