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Amazon Kinesis vs Starburst Galaxy comparison

 

Comparison Buyer's Guide

Executive Summary

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

Amazon Kinesis
Ranking in Streaming Analytics
11th
Average Rating
8.0
Reviews Sentiment
7.0
Number of Reviews
29
Ranking in other categories
No ranking in other categories
Starburst Galaxy
Ranking in Streaming Analytics
8th
Average Rating
9.4
Reviews Sentiment
2.5
Number of Reviews
11
Ranking in other categories
Data Science Platforms (7th)
 

Mindshare comparison

As of August 2026, in the Streaming Analytics category, the mindshare of Amazon Kinesis is 4.0%, down from 7.6% compared to the previous year. The mindshare of Starburst Galaxy is 1.7%, up from 1.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Starburst Galaxy1.7%
Amazon Kinesis4.0%
Other94.3%
Streaming Analytics
 

Featured Reviews

reviewer1480695 - PeerSpot reviewer
Director of Software Development at a tech vendor with 10,001+ employees
Has enabled real-time processing of critical event streams with seamless cloud integration
We are contemplating moving away from Amazon Kinesis primarily because of the cost. It is very useful, but if we write our own analytics and data processing pipeline, it would be much cheaper for us. The cost is a primary hindrance. That's why we are not using it widely. For our critical pipeline we are using it, but after that we are putting it in an S3 bucket. Other pipelines directly put the events in an S3 bucket and then process from there. There is no lack of functions in Amazon Kinesis. Functionality-wise, we feel it's complete. The cost aspect is what we are really concerned about.
NK
Advisory Solutions Architect at Dell Technologies
Unified data querying has accelerated petabyte-scale analytics and simplified dashboard delivery
Starburst Galaxy offers me several best features, which include very fast querying results, automatic indexing of data for long tables, a cost-based optimizer which reduces the time to query large tables, and an agentic feature that lets me talk to my data.I find myself relying most on querying from different databases as well as automatic indexing in my day-to-day work, as I am a data science architect who needs to get the queries in a very short period of time. Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best. Starburst Galaxy has positively impacted my organization since we were struggling with Denodo and Dremio, which had their own features but were not helpful in querying large amounts of data, especially semi-structured or unstructured data. Starburst Galaxy addresses this with many YAML files and manifest files for automated maintenance, and it helps reduce the small file problem in different HDFS systems. Additionally, Starburst Galaxy has an MCP server that connects to various agentic pipelines, reducing the time to market for data consumption.

Quotes from Members

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

Pros

"We have been able to drop our costs for ingesting data by about 60 to 70%."
"One of the best features of Amazon Kinesis is the multi-partition."
"Kinesis replaced a whole tier of servers, so we didn't need to have a server to catch the data and then send the data somewhere else, because Kinesis was the input port for very large amounts of data."
"Amazon Kinesis is easy to get started with, provides good documentation, and has a multilang daemon interface that makes it programming-language agnostic."
"Kinesis has the best of Amazon: data streaming, building processes, data analytics, data in real-time are very good."
"We have seen a return on our investment with Amazon Kinesis, as we are able to process data without any issue and it is our solution for ingesting data in other databases, such as Snowflake."
"I find almost all features valuable, especially the timing and fast pace movement."
"I find data Firehose and data streams are much more intelligent than other streaming solutions."
"The most fundamental feature is the query engine, which is much faster than any of the competitors; Starburst is able to finish most queries within 10 seconds, which is especially important for many non-technical employees."
"Starburst Galaxy serves the best purpose for me because if my SLAs are not met with my customers, they will raise a case, and I have tried many other tools, but Starburst Galaxy fits the best."
"Starburst Galaxy serves as our primary SQL-based data processing engine, a strategic decision driven by its seamless integration with our AWS cloud infrastructure and its ability to deliver high performance with low-latency responses."
"I use Starburst as a cost-efficient hosted option for Trino for data integration and ad-hoc analysis across a broad range of data sources."
"Starburst Galaxy has significantly improved our data architecture flexibility and performance management by solving cross-database query challenges and enabling us to utilize iceberg tables externally across our entire data ecosystem."
"Starburst Galaxy has positively impacted my organization by allowing us to rethink the strategy for data and architect data differently; instead of having multiple data marts and siloed data marts, we have a unified vision, and that is how it is changing."
"Starburst on Trino, combined with our SQL-native data transformation tool SQLMesh, has delivered anywhere from a two to five times improvement in compute performance across our transformation DAG."
"Starburst has provided us with virtually guaranteed performance on complex queries across datasets that are in the tens of gigabytes which complete in seconds."
 

Cons

"It would be beneficial if Amazon Kinesis provided document based support on the internet to be able to read the data from the Kinesis site."
"Kinesis can be expensive, especially when dealing with large volumes of data."
"There are some kind of hard limits on Amazon Kinesis, and if you hit that, then you will get the throughput exceed error."
"We were charged high costs for the solution’s enhanced fan-out feature."
"The price is not much cheaper. So, there is room for improvement in the pricing."
"The technical support could be improved. They tend to send you back to the documentation."
"There are certain shortcomings in the machine learning capacity offered by the product, making it an area where improvements are required."
"The solution has a two-minute maximum time delay for live streaming, which could be reduced."
"Multi-tenancy could be improved. In order to have multiple environments for SSO, we maintain multiple tenants that are connected to different AWS accounts via the Marketplace."
"Cluster startup time is another pain point, typically 3 to 5 minutes, which is not the worst with proper planning but can be annoying for ad-hoc work."
"I think there are areas of improvement with respect to AI adaptability, and also in general, the amount of connectors working with other tools are areas where it can be expanded."
"I would like to see better alerting integrations for failures and errors in scheduled tasks and maintenance jobs."
"Cluster startup time can be slow, sometimes taking over a minute."
"The most persistent issue is the cluster spin-up time."
"As a hosted option, I wish I had more control over the cluster configuration, specifically regarding some of the more advanced options."
"Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose."
 

Pricing and Cost Advice

"Under $1,000 per month."
"The tool's pricing is cheap."
"The fee is based on the number of hours the service is running."
"I think for us, with Amazon Kinesis, if we have to set up our own Kafka or cluster, it will be very time-consuming. If one considers the aforementioned aspect, Amazon Kinesis is a cheap tool."
"The pricing depends on the use cases and the level of usage. If you wanted to use Kinesis for different use cases, there's definitely a cheaper base cost involved. However, it's not entirely cheap, as different use cases might require different levels of Kinesis usage."
"The tool's entry price is cheap. However, pricing increases with data volume."
"I rate the product price a five on a scale of one to ten, where one is cheap, and ten is expensive."
"The product falls on a bit of an expensive side."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Computer Software Company
10%
Manufacturing Company
7%
Outsourcing Company
6%
Financial Services Firm
28%
Computer Software Company
11%
Construction Company
7%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business8
Midsize Enterprise10
Large Enterprise10
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise2
Large Enterprise3
 

Questions from the Community

What is your experience regarding pricing and costs for Amazon Kinesis?
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
What needs improvement with Amazon Kinesis?
We are contemplating moving away from Amazon Kinesis primarily because of the cost. It is very useful, but if we write our own analytics and data processing pipeline, it would be much cheaper for u...
What is your primary use case for Amazon Kinesis?
We use Amazon Kinesis for stream processing. We get events from on-premise devices to the cloud. We get many device events and we have to process these events that are coming from the devices. To p...
What is your experience regarding pricing and costs for Starburst Galaxy?
I recommend experimenting with different cluster sizes to determine what works best for your particular use case.
What needs improvement with Starburst Galaxy?
Starburst Galaxy can be improved by discovering unstructured data and building in streaming ingestion because we are currently using Kafka for that purpose. We rely on third-party tools for ingesti...
What is your primary use case for Starburst Galaxy?
My main use case for Starburst Galaxy is querying petabytes of data across vast data sources, and I use a federated query engine to join data sources from different databases and then join them usi...
 

Also Known As

Amazon AWS Kinesis, AWS Kinesis, Kinesis
No data available
 

Overview

 

Sample Customers

Zillow, Netflix, Sonos
Information Not Available
Find out what your peers are saying about Amazon Kinesis vs. Starburst Galaxy and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.