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Apache Hadoop vs Vertica comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Hadoop
Ranking in Data Warehouse
6th
Average Rating
7.8
Number of Reviews
39
Ranking in other categories
No ranking in other categories
Vertica
Ranking in Data Warehouse
4th
Average Rating
8.2
Reviews Sentiment
7.6
Number of Reviews
86
Ranking in other categories
Cloud Data Warehouse (7th)
 

Mindshare comparison

As of November 2024, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.1%, down from 6.2% compared to the previous year. The mindshare of Vertica is 9.3%, up from 9.1% 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

"Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."
"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."
"They have integrated other tools as well, like Power BI and Oracle BI, both on Azure, for reporting. Oracle BI is difficult to integrate."
"The solution is easy to expand. We haven't seen any issues with it in that sense. We've added 10 servers, and we've added two nodes. We've been expanding since we started using it since we started out so small. Companies that need to scale shouldn't have a problem doing so."
"I recommend it for the telecom sector. I know it well, and it's a good fit."
"I liked that Apache Hadoop was powerful, had a lot of tools, and the fact that it was free and community-developed."
"The performance is pretty good."
"The platform's quick data processing capabilities have been instrumental in supporting our AI-driven projects."
"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."
"It maximize cloud economics for mission-critical big data analytical initiatives."
"Vertica gives knowledgeable users and DBAs excellent tools for tuning."
"The product's initial setup phase is extremely simple."
"Speed and resiliency are probably the best parts of this product."
"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."
"The solution was executed quite quickly due to its columnar storage underground, which is the most valuable feature of our company"
"Any novice user can tune vertical queries with minimal training (or no training at all)."
 

Cons

"The load optimization capabilities of the product are an area of concern where improvements are required."
"The integration with Apache Hadoop with lots of different techniques within your business can be a challenge."
"Real-time data processing is weak. This solution is very difficult to run and implement."
"I mentioned it definitely, and this is probably the only feature we can improve a little bit because the terminal and coding screen on Hadoop is a little outdated, and it looks like the old C++ bio screen. If the UI and UX can be improved slightly, I believe it will go a long way toward increasing adoption and effectiveness."
"Hadoop lacks OLAP capabilities."
"It would be good to have more advanced analytics tools."
"I think more of the solution needs to be focused around the panel processing and retrieval of data."
"The solution is very expensive."
"Performance of management of metadata layer (database catalog) needs improvement. We still have to have smaller customers on PostgreSQL; Vertica cannot manage thousands of schemata."
"Limitations in group by projections is where I would like to see an improvement."
"The documentation of Vertica is an area with shortcomings where improvements are required."
"Very bad support, I would rate it two out of 10."
"Suboptimal projection design causes queries to not scale linearly."
"The biggest problem is the cost of cloud deployment."
"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."
"The integration of this solution with ODI could be improved."
 

Pricing and Cost Advice

"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."
"It's reasonable, but there's room for improvement in cost-effectiveness."
"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."
"The product is open-source, but some associated licensing fees depend on the subscription level."
"We just use the free version."
"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."
"​There are no licensing costs involved, hence money is saved on the software infrastructure​."
"This is a low cost and powerful solution."
"Vertica is an expensive tool."
"The solution is relatively cost-effective."
"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."
"The solution is free and we pay for the storage."
"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."
"The price of Vertica is less expensive than some competitors, such as Teradata."
"It's an expensive product"
"It is fast to purchase through the AWS Marketplace."
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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
32%
Computer Software Company
11%
University
7%
Energy/Utilities Company
6%
Computer Software Company
18%
Financial Services Firm
18%
Manufacturing Company
8%
University
5%
 

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
 

Learn More

 

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: November 2024.
816,406 professionals have used our research since 2012.