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Amazon Redshift vs Dremio comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Amazon Redshift
Ranking in Cloud Data Warehouse
4th
Average Rating
7.8
Reviews Sentiment
7.4
Number of Reviews
66
Ranking in other categories
No ranking in other categories
Dremio
Ranking in Cloud Data Warehouse
10th
Average Rating
8.6
Reviews Sentiment
5.9
Number of Reviews
6
Ranking in other categories
Data Science Platforms (8th)
 

Mindshare comparison

As of November 2024, in the Cloud Data Warehouse category, the mindshare of Amazon Redshift is 7.7%, down from 11.9% compared to the previous year. The mindshare of Dremio is 4.2%, up from 2.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Warehouse
 

Featured Reviews

Ved Prakash Yadav - PeerSpot reviewer
Works as a data warehouse system and collects data from different sources
In terms of improvement, I believe Amazon Redshift could work on reducing its costs, as they tend to increase significantly. Additionally, there are occasional issues with nodes going down, which can be problematic. We often encounter issues like someone dropping a column or changing the order of columns, which can cause synchronization problems when pushing data through our pipeline. It's a minor issue, but it can be annoying.
MikeWalker - PeerSpot reviewer
It enables you to manage changes more effectively than any other platform.
Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it. There's another thing called data providence. They're tied together. Data providence allows you to go back and recreate the data at any particular point in time. It's extremely important for compliance and governance issues because data changes all time. How did it change? What was it three days or months ago? You may have made some decisions based on data that was three months old, so you might need to revisit those. It's essential for things like machine learning and deep learning, where you are generating AI models off data. When the model stops working or doesn't work as expected, you need to figure out why. You have to go back and adjust the datasets used to train the model. We do that through an open-source project called Nessie, which is their basis for providing data lineage and data province capabilities. It's super powerful. Arrow is another open-source project for storing data in memory and performing data query operations. Data sits on a disk in one format. If you want to do anything with data, you have to load it into your computer and put it into memory so you can work with it. Arrow provides a format in memory that enables the whole library to perform various operations on that data. Every vendor has its own way of representing data in memory. They've latched onto an industry standard and developed it so it's open. Now people can use the exact same format in memory to do operations and use the library set to perform functions on data. New developers can decide if they want to develop their own memory format or use one that's already there. Data transfer is a massive problem when you're working with large datasets, doing advanced analytics, and trying to train machine learning or deep learning models. What happens often is companies downsample their data sets to do training on models because transferring and managing data on a deep learning or machine learning platform is too much.

Quotes from Members

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

Pros

"I am satisfied with the performance of the product."
"The initial setup of this solution is straightforward."
"Changing from local servers to the cloud is very easy. It's so nice not to have to worry about physical servers."
"The stability of Amazon Redshift is good."
"Amazon Redshift is a really powerful database system for reporting and data warehousing."
"Its simplicity in configuration, cost-effectiveness due to being in the cloud and close to our data sources, and the fact that it's a managed service that is scalable and reliable are highly valuable."
"Has a very user-friendly SQL editor and it's very easy to use the connectors."
"The valuable features are performance, data compression, and scalability."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"We primarily use Dremio to create a data framework and a data queue."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Dremio allows querying the files I have on my block storage or object storage."
 

Cons

"The refreshment rate of data reaching Redshift from other sources should be faster."
"Query compilation time needs a lot of improvement for cases where you are generating queries dynamically."
"Pricing is one of the things that it could improve. It should be more competitive."
"Planting is the primary key enforcement that should be improved."
"There are physically too many pipelines for a company of this size to maintain. For a data scientist, it's very difficult to learn the data in all of these different environments."
"In the next release, a pivot function would be a big help. It could save a lot of time creating a query or process to handle operations."
"I would like to improve the pricing and the simplicity of using this solution."
"There might be some limitations from a business intelligence perspective, but nothing we can't find a workaround for."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"It shows errors sometimes."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
 

Pricing and Cost Advice

"The price of the solution is reasonable. According to the RA3 cluster particularly, it provides 128 GB of storage with only four nodes. If you can manage your computations processes with the help of materialized views and proper queries. I think the IP clusters are very useful and overall fair for the price."
"Amazon Redshift is an expensive solution. Larger organizations can afford this solution, but smaller businesses would struggle to afford it."
"My customers have implementations that cost about $500 a month for a very small one. I also have a customer with a monthly invoice of about $25,000 USD."
"One of my customers went with Google Big Query over Redshift because it was significantly cheaper for their project."
"The best part about this solution is the cost."
"The solution is available at a mid-range price compared to other vendors."
"The part that I like best is that you only pay for what you are using."
"The price of Amazon Redshift is reasonable because it depends on the usage that you use and for DWH for the long term."
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
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Top Industries

By visitors reading reviews
Educational Organization
60%
Financial Services Firm
7%
Computer Software Company
6%
Manufacturing Company
4%
Financial Services Firm
32%
Computer Software Company
10%
Manufacturing Company
8%
Retailer
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

How does Amazon Redshift compare with Microsoft Azure Synapse Analytics?
Amazon Redshift is very fast, has a very good response time, and is very user-friendly. The initial setup is very straightforward. This solution can merge and integrate well with many different dat...
What do you like most about Amazon Redshift?
The tool's most valuable feature is its parallel processing capability. It can handle massive amounts of data, even when pushing hundreds of terabytes, and its scaling capabilities are good.
What is your experience regarding pricing and costs for Amazon Redshift?
You can start small with a basic cluster to learn and practice with it. Selecting the most basic and economical cluster type can save you enough money to move forward with the solution or go with a...
What do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
Every tool has a value based on its visualization, and the pricing is worth its value.
What needs improvement with Dremio?
Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I cannot use the recursive common table expression (CTE) in Dremio because the supp...
 

Comparisons

 

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Sample Customers

Liberty Mutual Insurance, 4Cite Marketing, BrandVerity, DNA Plc, Sirocco Systems, Gainsight, Blue 449
UBS, TransUnion, Quantium, Daimler, OVH
Find out what your peers are saying about Amazon Redshift vs. Dremio and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.