Software AG Apama vs Upsolver comparison

Why PeerSpot?

Software AG and Upsolver are both solutions in the Streaming Analytics category. Software AG is ranked #25, while Upsolver is ranked #21 with an average rating of 8.7. Software AG holds a 1.6% mindshare in SA, compared to Upsolver’s 1.3% mindshare. Additionally, 100% of Software AG users are willing to recommend the solution, compared to 100% of Upsolver users who would recommend it.

Software AG Apama

Read 1 Software AG Apama review

1,058 Views
846 Comparison Views

100% willing to recommend

Upsolver

Read 4 Upsolver reviews

2,226 Views
557 Comparison Views

100% willing to recommend

Software AG Apama

Upsolver

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Software AG Apama and Upsolver based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Microsoft, Apache and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: September 2026).

Buyer's Guide

Streaming Analytics

September 2026

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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

Software AG Apama

Ranking in Streaming Analytics

25th

Average Rating

7.0

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

Complex Event Processing (CEP) (3rd)

Upsolver

Ranking in Streaming Analytics

21st

Average Rating

8.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Integration (38th)

Mindshare comparison

As of September 2026, in the Streaming Analytics category, the mindshare of Software AG Apama is 1.6%, up from 0.4% compared to the previous year. The mindshare of Upsolver is 1.3%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Mindshare Distribution
Product	Mindshare (%)
Upsolver	1.3%
Software AG Apama	1.6%
Other	97.1%

Streaming Analytics

Featured Reviews

Shekhar Pathak

Sr Executive Accounts at a computer software company with 1,001-5,000 employees

A tool to send out promotional notifications that need to improve areas, like deployment and maintenance

Software AG Apama should support offline scenarios as it may not always be possible to stay connected with the cloud. The solution should be deployed on an on-premises model, and it should be able to handle offline scenarios. If certain rules are set in Software AG Apama, then it should be able to execute them without being connected to an open internet source. With Software AG Apama, one may face challenges since it is difficult to find people with the right skill set to operate it. The solution also makes use of a proprietary programming language that is hard to trace in the market. It is better to go with the new options available in the market since Software AG Apama has become an old product. The ease of development and maintenance should be enhanced, but it is difficult due to the use of the proprietary programming language in the product.

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reviewer2784462

Software Engineer at a tech vendor with 10,001+ employees

Streaming pipelines have become simpler and onboarding new data sources is now much faster

One of the best features Upsolver offers is the automatic schema evolution. Another good feature is SQL-based streaming transformations. Complex streaming transformations such as cleansing, deduplication, and enrichment were implemented using SQL and drastically reduced the need for custom Spark code. My experience with the SQL-based streaming transformations in Upsolver is that it had a significant positive impact on the overall data engineering workflow. By replacing custom Spark streaming jobs with declarative SQL logic, I simplified development, review, and deployment processes. Data transformations such as parsing, filtering, enrichment, and deduplication could be implemented and modified quickly without rebuilding or redeploying complex code-based pipelines. Upsolver has impacted my organization positively because it brings many benefits. The first one is faster onboarding of new data sources. Another one is more reliable streaming pipelines. Another one is near-real-time data availability, which is very important for us. It also reduced operational effort for data engineering teams. A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days. Custom Spark code reduction reached 50 to 40 percent. Pipeline failures are reduced by 70 to 80 percent. Data latency is improved from hours to minutes.

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Quotes from Members

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

Pros

"The most valuable feature of the solution is the ability that it provides its users to handle different kinds of rules."

"A specific outcome that highlights these benefits is that the time to onboard new sources is reduced from weeks to days, custom Spark code reduction reached 50 to 40 percent, pipeline failures are reduced by 70 to 80 percent, and data latency is improved from hours to minutes."

"I have saved 50 to 60% on maintaining pipelines since using Upsolver."

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

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

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

Cons

"The ease of development and maintenance should be enhanced, but it is difficult due to the use of the proprietary programming language in the product."

"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."

"I think that Upsolver can be improved in orchestration because it is not a full orchestration tool."

"I would say Upsolver's scalability is eight out of 10 because of pricing."

"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."

Pricing and Cost Advice

"A commercial license is required to operate Software AG Apama."

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

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Top Industries

By visitors reading reviews

No data available

Real Estate/Law Firm

14%

Manufacturing Company

14%

Retailer

13%

Construction Company

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

Ask a question

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What is your experience regarding pricing and costs for Upsolver?

My experience with pricing, setup cost, and licensing is that the pricing is nine out of 10.

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What needs improvement with Upsolver?

I think Upsolver can be improved with deeper integration with external orchestration out of the box. I would appreciate more clear dashboards with billing in real time as a needed improvement.

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What is your primary use case for Upsolver?

My main use case for Upsolver is to operate with changes in the structure of new data without a pipeline disrupting. I write SQL queries in Upsolver, and the platform takes care of the data itself,...

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Compared 16% of the time

IBM Operational Decision Manager vs Software AG Apama

Compared 15% of the time

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Compared 7% of the time

SAS Access vs Upsolver

Compared 6% of the time

Alteryx Designer vs Upsolver

Compared 5% of the time

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Product Reports

Buyer's Guide

Streaming Analytics

September 2026

Download Software AG Apama product report

Buyer's Guide

Data Integration

September 2026

Download Upsolver product report

Also Known As

Progress Apama

No data available

Overview

Software AG Apama is an advanced complex event processing platform designed to enable real-time analytics and intelligent decision-making across industries.

Software AG Apama provides a comprehensive suite for data processing, offering decision automation and analytics capabilities. It handles high-frequency data streams efficiently, catering to businesses needing swift responses and actionable insights for better performance. Its robust infrastructure supports dynamic applications, particularly in environments requiring rapid data processing.

What are the key features of Software AG Apama?

Real-time Analytics: Provides immediate insights to drive time-sensitive decisions.
Scalability: Easily adapts to growing data demands without compromising performance.
Event Processing Language: Offers a domain-specific language for developing event-driven applications efficiently.
Integration Capabilities: Seamlessly connects with other enterprise systems for expanded functionality.
Visualization Tools: Delivers user-friendly dashboards for monitored analysis.

What benefits and ROI should users consider?

Enhanced Decision Making: Allows for swift data interpretation and informed decisions.
Increased Efficiency: Automation of complex processes saves time and resources.
Improved Performance: Optimizes event processing, reducing latency in data handling.
Fast Time to Market: Accelerates development and deployment cycles.
Cost Reduction: Minimizes the need for additional resources through efficient data management.

Software AG Apama is widely used in financial services for high-frequency trading and fraud detection. Retail industries leverage it for real-time customer analytics and supply chain optimization. In telecommunication, it enhances network data analysis for better service management and customer satisfaction.

Software AG

Upsolver offers a data lakehouse platform that simplifies big data processing and analytics, enabling data teams to efficiently handle large-scale datasets.

Upsolver's platform focuses on simplifying the complexities of data engineering by transforming raw data into queryable formats quickly. It allows seamless integration with cloud storage and various database systems, providing flexibility for data-driven businesses. The platform automates data preparation tasks, reducing manual coding and allowing teams to focus on extracting insights. Its scalable architecture supports real-time analytics and batch processing.

What are the key features of Upsolver?

Data Ingestion: Easily ingest data from multiple sources with minimal configuration.
Schema On-Read: Automatically interpret data schemas, simplifying data management.
Streaming SQL: Transform and analyze streaming data using a familiar SQL syntax.
Data Lake Integration: Seamlessly connect with data lakes for streamlined workflows.

What benefits and ROI should users consider?

Time Savings: Faster data processing reduces time to insights.
Cost Efficiency: Scalable architecture optimizes infrastructure costs.
Scalability: Handle growing data volumes effortlessly.
Flexibility: Supports wide data storage and processing strategies.

In the e-commerce industry, Upsolver helps businesses optimize their data pipelines for better customer segmentation and personalization, while in finance, it enhances fraud detection capabilities through real-time data analytics.

Upsolver

Sample Customers

Okasan Online Securities

Information Not Available

Find out what your peers are saying about Databricks, Microsoft, Apache and others in Streaming Analytics. Updated: September 2026.

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