Apache Hadoop vs Vertica comparison

Apache and OpenText are both solutions in the Data Warehouse category. Apache is ranked #7 with an average rating of 7.9, while OpenText is ranked #5 with an average rating of 8.0. Apache holds a 5.1% mindshare in Data Warehouse, compared to OpenText’s 8.5% mindshare. Additionally, 89% of Apache users are willing to recommend the solution, compared to 91% of OpenText users who would recommend it.

Apache Hadoop

Read 40 Apache Hadoop reviews

1,323 Views
1,068 Comparison Views

89% willing to recommend

Vertica

Read 86 Vertica reviews

2,233 Views
1,718 Comparison Views

91% willing to recommend

Apache Hadoop

Vertica

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Executive SummaryUpdated on Dec 18, 2024

Vertica and Apache Hadoop compete in the data management and analytics category. Vertica appears to have the upper hand due to its advanced analytical features and faster query performance.

Features: Vertica is known for quick data loading, robust clustering for commodity hardware, and efficient data compression. Its support for OLAP allows concurrent access and scalability without load time concerns. The interface is intuitive for SQL queries, enhanced by columnar storage and parallel processing. Apache Hadoop excels in processing diverse data types efficiently through a strong distributed file system, offering great flexibility for handling big data and various data formats.

Room for Improvement: Vertica faces challenges with transaction-heavy workloads and needs improvements in workload management and data replication. Extensive maintenance and limited direct database integration are drawbacks, along with the need for better developer tools. For Apache Hadoop, redundancy configurations and rolling restarts need enhancement, as well as real-time processing capabilities and integration with visualization tools.

Ease of Deployment and Customer Service: Vertica offers flexible deployment options including on-premises and hybrid cloud setups, with generally positive customer service feedback but some variability in technical support. Apache Hadoop supports diverse environments but can be complex to deploy without community guidance. User experiences with technical support vary depending on expertise with open-source tools.

Pricing and ROI: Vertica provides flexible pricing based on data size, seen as cost-effective due to its performance, with a community edition for trials. Apache Hadoop, as an open-source solution, offers cost-effectiveness but costs may vary with third-party subscriptions, leading to less immediate ROI due to integration and maintenance complexities.

To learn more, read our detailed Apache Hadoop vs. Vertica Report (Updated: April 2025).

Buyer's Guide

Apache Hadoop vs. Vertica

April 2025

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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

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

Ranking in other categories

Cloud Data Warehouse (11th)

Mindshare comparison

As of May 2025, in the Data Warehouse category, the mindshare of Apache Hadoop is 5.1%, down from 5.6% compared to the previous year. The mindshare of Vertica is 8.5%, down from 8.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Q&A Highlights

it_user1272297

Special Adviser Strategy at a university with 501-1,000 employees

Apr 19, 2020

Which is the best RDMBS solution for big data?

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

See all answers

Featured Reviews

Sushil Arya

Software developer at Fiserv

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.

Read full review

T Venkatesh

Deputy Manager at ICICIBANK Ltd

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…

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Quotes from Members

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

Pros

"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."

"It is a file system for data collection. There are nodes in this cluster that contain all the information, directories, and other files. The nodes are based on the MySQL database."

"Its integration is Hadoop's best feature because that allows us to support different tools in a big data platform."

"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."

"Hadoop is extensible — it's elastic."

"The most valuable feature is the database."

"Its flexibility in handling and storing large volumes of data is particularly beneficial, as is its resilience, which ensures data redundancy and fault tolerance."

More Apache Hadoop pros

"The solution was executed quite quickly due to its columnar storage underground, which is the most valuable feature of our company"

"Vertica gives knowledgeable users and DBAs excellent tools for tuning."

"The initial setup was straightforward."

"The performance is very good and the aggregate records are fast."

"Any novice user can tune vertical queries with minimal training (or no training at all)."

"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."

"The most valuable feature of Vertica is the ability to receive large aggregations at a very quick pace. The use case of subclusters is very good."

"The Vertica architecture means it can process/ingest data in parallel to reporting and analyzing because of its in-memory Write-Optimized Storage sitting alongside the analytics optimized Read-Optimized Storage."

More Vertica pros

Cons

"The load optimization capabilities of the product are an area of concern where improvements are required."

"The solution could use a better user interface. It needs a more effective GUI in order to create a better user environment."

"Hadoop lacks OLAP capabilities."

"Real-time data processing is weak. This solution is very difficult to run and implement."

"It could be more user-friendly."

"There is a lack of virtualization and presentation layers, so you can't take it and implement it like a radio solution."

"The key shortcoming is its inability to handle queries when there is insufficient memory. This limitation can be bypassed by processing the data in chunks."

"In the next release, I would like to see Hive more responsive for smaller queries and to reduce the latency."

More Apache Hadoop cons

"I would personally like to see extended developer tooling suited to Vertica – think published PowerDesigner SQL dialect support."

"Whatever's out, the core is not always as great as the engine, especially their first version."

"There are a lot of limitations within this product and it makes things extremely hard for developers. It lacks Stored Procedure, packages, and triggers like other RDBMs."

"In a future release, we would like to have artificial intelligence capabilities like neural networks. Customers are demanding this type of analytics."

"The documentation of Vertica is an area with shortcomings where improvements are required."

"I believe the installation process could be streamlined."

"The product could improve by adding support for a wider variety of data types and enhancing features to better compete with other databases."

"Documentation has become much better, but can always use some improvement."

More Vertica cons

Pricing and Cost Advice

"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 price of Apache Hadoop could be less expensive."

"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."

"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."

"The price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."

More Apache Hadoop pricing and cost advice

"The pricing for this solution is very reasonable compared to other vendors."

"It's free up to three nodes and 1TB, and then get in contact with their sales guys."

"The solution is relatively cost-effective."

"It is fast to purchase through the AWS Marketplace."

"Read the fine print carefully."

"It's an expensive product"

"The pricing and licensing depend on the size of your environment and the zone where you want to implement."

"The price is reasonable. We use a pay per license model. Firstly, you need to buy a license. After that, you mainly pay the annual support fee of around 20% or 25%. I think their prices are quite reasonable."

More Vertica pricing and cost advice

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Answers from the Community

it_user1272297

Special Adviser Strategy at a university with 501-1,000 employees

Apr 19, 2020

Which is the best RDMBS solution for big data?

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

Founder and CEO at PeerSpot

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.

Read full answer

reviewer1219965

Data Architect at a tech services company with 201-500 employees

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

Read full answer

See all 4 answers

Top Industries

By visitors reading reviews

Financial Services Firm

33%

Computer Software Company

11%

University

Energy/Utilities Company

Financial Services Firm

19%

Computer Software Company

18%

Manufacturing Company

University

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.

See all answers

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...

See all answers

What needs improvement with Apache Hadoop?

The problem with Apache Hadoop arose when the guys that originally set it up left the firm, and the group that later owned it didn't have enough technical resources to properly maintain it. This wa...

See all answers

What do you like most about Vertica?

Vertica is easy to use and provides really high performance, stability, and scalability.

See all answers

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.

See all answers

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.

See all answers

Comparisons

Oracle Exadata vs Apache Hadoop

Compared 21% of the time

Teradata vs Apache Hadoop

Compared 13% of the time

Azure Data Factory vs Apache Hadoop

Compared 13% of the time

BigQuery vs Apache Hadoop

Compared 11% of the time

SAP IQ vs Apache Hadoop

Compared 5% of the time

More Apache Hadoop Competitors

SQL Server vs Vertica

Compared 14% of the time

Teradata vs Vertica

Compared 12% of the time

Oracle Exadata vs Vertica

Compared 9% of the time

Snowflake vs Vertica

Compared 9% of the time

Yellowbrick Data Warehouse vs Vertica

Compared 2% of the time

More Vertica Competitors

Product Reports

Buyer's Guide

Apache Hadoop

April 2025

Download Apache Hadoop product report

Buyer's Guide

Vertica

April 2025

Download Vertica product report

Also Known As

No data available

Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand

Overview

The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Apache

Vertica is a deploy-anywhere SQL database created for elasticity, speed, and advanced analytics. Vertica enables today’s busy teams to modernize their data warehouses, democratize data and analytics to enable increased access, and deploy analytics in a hybrid cloud environment. Additionally, Vertica merges how companies power their analytics by providing a scalable, open, and elastic database with numerous intuitive features.

In today’s marketplace, organizations are experiencing continued robust growth of data volumes, and citizen data scientists’ broader use of analytics is causing many companies to re-visit and re-examine their systems in order to match the demands of an aggressive marketplace. Analytics are continually swiftly evolving. New data from social media, blogs, IoT sources, data streams, gas and electrical grids, and mobile networks is being constantly gathered in extensive data sets. This presents organizations with a new opportunity to become more data driven, and they must be able to manage the new data growth and identify the trends and sequences that can lead to both improved business opportunities and continued repeat business from their clients.

Vertica Benefits:

Vertica has many valuable key benefits. Some of its most useful benefits include:

Efficiency: Vertica provides robust compression and intuitive impressions. This results in users requiring significantly less storage and hardware than other comparable data analytics solutions. The progressive Vertica architecture results in queries that are 10-50 times faster than other platforms while providing more storage data per server.
Integration: Each new iteration of Vertica is tested and certified with the latest ETL and visualization tools. It actively supports Java Database Connectivity (JDBC), Open Database Connectivity (ODBC), and popular SQL providers. All these solutions and most leading BI and visualization tools interact seamlessly, making Vertica overall a very cost-effective solution and solid business investment.
Cloud flexibility: With Vertica, users do not have to get locked into a single cloud vendor. Users are able to take complete advantage of the current infrastructure that is already in place. Vertica seamlessly integrates with popular public clouds, including Google Cloud Platform (GCP), Azure, AWS, Alibaba, VMware clouds, and more. It also provides for easy portability across on-premise and multi-cloud environments and data lakes. Vertica designs a robust flexible platform for running a company’s analytical and computing workloads, which allows applications to run simultaneously on numerous environments in a hybrid cloud infrastructure. Vertica is able to seamlessly use public clouds and private data centers, and it grants the flexibility to switch in an instant.
Security: Vertica offers dynamic end-to-end security with support for partner solutions and industry-standard protocols such as Apache Sentry, AWS IAM, Kerberos, LDAP, and more. Vertica utilizes an intuitive layered security model that provides multiple security authentication authorization mechanisms. Vertica will also maintain an audit trail, natively exported to other security domains for analysis and persistence.

Reviews from Real Users

“I am using Vertica for aggregations and dashboards. The most valuable feature of Vertica is the ability to receive large aggregations at a very quick pace. The use case of subclusters is very good.” - Bijal S., Group Chief Technology Officer at Netcore Solutions

“The hardware usage and speed has been the most valuable feature of this solution. It is very fast and has saved us a lot of money.” - Munkhsaikhan B., Project Lead - Digital Transformation Unit at Bodi Electronics LLC

OpenText

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.

Buyer's Guide

Apache Hadoop vs. Vertica

April 2025

Free Report: Apache Hadoop vs. Vertica

Find out what your peers are saying about Apache Hadoop vs. Vertica and other solutions. Updated: April 2025.

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