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Apache Hadoop vs Vertica comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 18, 2024

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 Hadoop
Ranking in Data Warehouse
7th
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
40
Ranking in other categories
No ranking in other categories
Vertica
Ranking in Data Warehouse
5th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
86
Ranking in other categories
Cloud Data Warehouse (11th)
 

Mindshare comparison

As of April 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.0%, down from 5.7% compared to the previous year. The mindshare of Vertica is 8.6%, down from 8.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Warehouse
 

Q&A Highlights

it_user1272297 - PeerSpot reviewer
Apr 19, 2020
 

Featured Reviews

Sushil Arya - PeerSpot reviewer
Provides ease of integration with the IT workflow of a business
When working with Kafka, I saw that the data came in an incremental order. The incremental data processing part is still not very effective in Apache Hadoop. If the data is already there, it can be processed very effectively, especially if the data is coming in every second. If you want to know the location of some data every second, then such data is not processed effectively in Apache Hadoop. I can say that one of the features where improvements are required revolves around the licensing cost of the tool. If the tool can build some licensing structures in a pay-per-use manner, organizations can get the look and feel of Apache Hadoop. Apache Hadoop can offer a licensing structure of the product that can be seen as similar to how AWS operates. Apache Hadoop can look into the capability of processing incremental data. The tool's setup process can be a scope of improvement. Also, it is not very simple because while doing the setup, we need to do all the server settings, including port listing and firewall configurations. If we look at other products on the market, then they can be made simpler. There are certain shortcomings when it comes to the product's technical support part, making it an area where improvements are required. The time frame for the resolution is an area that needs to be improved. The overall communication part of the technical support team also needs improvement.
T Venkatesh - PeerSpot reviewer
Processes query faster through multiple systems simultaneously, but it could support different data types
We use the solution for various tasks, including preparing data marts and generating offers. It helps extract data based on rules from the policy team and provides insights to enhance business operations. We also analyze transactions to target customers and improve business performance The…

Quotes from Members

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

Pros

"Hadoop is extensible — it's elastic."
"The most valuable features are the ability to process the machine data at a high speed, and to add structure to our data so that we can generate relevant analytics."
"Apache Hadoop is crucial in projects that save and retrieve data daily. Its valuable features are scalability and stability. It is easy to integrate with the existing infrastructure."
"Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability."
"Most valuable features are HDFS and Kafka: Ingestion of huge volumes and variety of unstructured/semi-structured data is feasible, and it helps us to quickly onboard a new Big Data analytics prospect."
"Its flexibility in handling and storing large volumes of data is particularly beneficial, as is its resilience, which ensures data redundancy and fault tolerance."
"Two valuable features are its scalability and parallel processing. There are jobs that cannot be done unless you have massively parallel processing."
"What I like about Apache Hadoop is that it's for big data, in particular big data analysis, and it's the easier solution. I like the data processing feature for AI/ML use cases the most because some solutions allow me to collect data from relational databases, while Hadoop provides me with more options for newer technologies."
"The initial setup was straightforward."
"Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression."
"Bulk loads, batch loads, and micro-batch loads have made it possible for our organization to process near real-time ingestions and faster analytics."
"We are able to integrate our Vertica data warehouse with Tableau to create numerous reports quickly and efficiently."
"Vertica is a columnar database where the query performance is extremely fast and it can be used for real-time integrations for API and other applications. The solution requires zero maintenance which is helpful."
"For me, It's performance, scalability, low cost, and it's integrated into enterprise and big data environments."
"Vertica is a great product because customers can compress and code data. The infrastructure that data warehouse solutions need is a commodity server so that customers don't have to invest in infrastructure."
"I don't need any special hardware. I can use commodity hardware, which is nice to have in a commercial solution."
 

Cons

"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"Since it is an open-source product, there won't be much support."
"Improvements in security measures would be beneficial, given the large volumes of data handled."
"The upgrade path should be improved because it is not as easy as it should be."
"I would like to see more direct integration of visualization applications."
"The solution needs a better tutorial. There are only documents available currently. There's a lot of YouTube videos available. However, in terms of learning, we didn't have great success trying to learn that way. There needs to be better self-paced learning."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"Vertica offers a platform-as-a-service version, but their software-as-a-service solution is only available on AWS. They need to get a SaaS version on Azure and GCP as fast as possible."
"It should provide a GUI interface for data management and tuning."
"In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics."
"Support is an area where it could get better."
"I would personally like to see extended developer tooling suited to Vertica – think published PowerDesigner SQL dialect support."
"It's hard to make it slow for a small data volume. For large volumes, it's hard to make it work. It's also hard to make it faster, and to make it scale."
"Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be."
"We are looking for a cheaper deployment for the solution. Although we did a lot of benchmarks, like Redshift. We tried Redshift, it didn't work. It didn't work out for us as well."
 

Pricing and Cost Advice

"The price of Apache Hadoop could be less expensive."
"Do take into consider that data storage and compute capacity scale differently and hence purchasing a "boxed" / 'all-in-one" solution (software and hardware) might not be the best idea."
"If my company can use the cloud version of Apache Hadoop, particularly the cloud storage feature, it would be easier and would cost less because an on-premises deployment has a higher cost during storage, for example, though I don't know exactly how much Apache Hadoop costs."
"We don't directly pay for it. Our clients pay for it, and they usually don't complain about the price. So, it is probably acceptable."
"This is a low cost and powerful solution."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"For any big enterprise the costs can be handled, and it is suitable for big enterprises because the scale of data is large. For medium and small enterprises, the tool is on the high-price side."
"Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October).​"
"Vertica has a perpetual license, but they are currently trying to convert all those licenses to subscription-based licenses on a yearly basis."
"It's an expensive product"
"I think it's starting to get a little expensive. Open source products are starting to get more robust, so I think that's something that they need to start looking at in terms of licensing."
"I am aware that we have licensed it, but I have no knowledge of its cost."
"The pricing for this solution is very reasonable compared to other vendors."
"Read the fine print carefully."
"The first TB is free and you can use all the Vertica features. After 1TB you have to pay for licensing. The product is worth it, but be aware of this condition, and plan. The compression ratio is explained in the documentation."
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Answers from the Community

it_user1272297 - PeerSpot reviewer
Apr 19, 2020
Apr 19, 2020
I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
2 out of 4 answers
Russell Rothstein - PeerSpot reviewer
Jan 27, 2020
Morten, the most popular comparisons of SQream can be found here: https://www.itcentralstation.com/products/sqream-db-alternatives-and-competitors The top ones include Cassandra, MemSQL, MongoDB, and Vertica.
reviewer1219965 - PeerSpot reviewer
Jan 27, 2020
I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
 

Top Industries

By visitors reading reviews
Financial Services Firm
34%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Financial Services Firm
20%
Computer Software Company
18%
Manufacturing Company
8%
Real Estate/Law Firm
4%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Hadoop?
It's primarily open source. You can handle huge data volumes and create your own views, workflows, and tables. I can also use it for real-time data streaming.
What is your experience regarding pricing and costs for Apache Hadoop?
The product is open-source, but some associated licensing fees depend on the subscription level. While it might be free for students, organizations typically need to pay for their subscriptions. Th...
What needs improvement with Apache Hadoop?
Hadoop lacks OLAP capabilities. I recommend adding a Delta Lake feature to make the data compatible with ACID properties. Also, video and audio streaming import issues could be improved to ensure p...
What do you like most about Vertica?
Vertica is easy to use and provides really high performance, stability, and scalability.
What is your experience regarding pricing and costs for Vertica?
The solution is relatively cost-effective. Pricing and licensing are reasonable compared to other solutions.
What needs improvement with Vertica?
The product could improve by adding support for a wider variety of data types and enhancing features to better compete with other databases.
 

Comparisons

 

Also Known As

No data available
Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
 

Overview

 

Sample Customers

Amazon, Adobe, eBay, Facebook, Google, Hulu, IBM, LinkedIn, Microsoft, Spotify, AOL, Twitter, University of Maryland, Yahoo!, Cornell University Web Lab
Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.
Find out what your peers are saying about Apache Hadoop vs. Vertica and other solutions. Updated: February 2025.
842,767 professionals have used our research since 2012.