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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 designed to be scalable, so I don't think that it has limitations in regards to scalability."
"The tool's stability is good."
"Its flexibility in handling and storing large volumes of data is particularly beneficial, as is its resilience, which ensures data redundancy and fault tolerance."
"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"Hadoop is a distributed file system, and it scales reasonably well provided you give it sufficient resources."
"One valuable feature is that we can download data."
"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."
"The most valuable feature is the database."
"I appreciate the flexibility offered by Vertica's projections. It allows for modifying the primary projection without altering the tables, which helps to optimize queries without the need to modify the underlying data."
"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."
"Vertica has a few features that I like. From an architecture standpoint, they have separated compute and storage. So you have low-cost object storage for primary storage and the ability to have several sub-clusters working off the same ObjectStore. So it provides workload isolation."
"The fast columnar store database structure allows our query times to be at least 10x faster than on any other database."
"It maximize cloud economics for mission-critical big data analytical initiatives."
"Initiate on one node, and the RPM propagates automatically to all other nodes. ​"
"It maximizes cloud economics with Eon Mode by scaling cluster size to meet variable workload demands."
"For me, It's performance, scalability, low cost, and it's integrated into enterprise and big data environments."
 

Cons

"We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."
"I would like to see more direct integration of visualization applications."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The solution is not easy to use. The solution should be easy to use and suitable for almost any case connected with the use of big data or working with large amounts of data."
"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."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"The solution is very expensive."
"From the Apache perspective or the open-source community, they need to add more capabilities to make life easier from a configuration and deployment perspective."
"Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down."
"The integration with AI has room for improvement."
"When it is about to reach the maximum storage capacity, it becomes slow."
"They could improve on customer service."
"They could improve the integration and some of the features in the cloud version."
"Monitoring tools need to be lightweight. They should not take up heavy resources of the main server."
"It should provide a GUI interface for data management and tuning."
"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."
 

Pricing and Cost Advice

"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."
"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."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"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."
"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
"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."
"The price of Apache Hadoop could be less expensive."
"We just use the free version."
"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."
"Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October).​"
"It's an expensive product"
"The pricing for this solution is very reasonable compared to other vendors."
"The pricing and licensing depend on the size of your environment and the zone where you want to implement."
"The pricing could improve, it is a little expensive."
"The solution is free and we pay for the storage."
"Read the fine print carefully."
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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.
844,944 professionals have used our research since 2012.