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 5.0% mindshare in Data Warehouse, compared to OpenText’s 8.6% 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

Comparison Buyer's Guide

Download the report

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: February 2025).

Buyer's Guide

Apache Hadoop vs. Vertica

February 2025

Download the complete report

Helped 844,944 peers since 2012

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 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

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…

Read full review

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."

More Apache Hadoop pros

"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."

More Vertica pros

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."

More Apache Hadoop cons

"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."

More Vertica cons

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."

More Apache Hadoop pricing and cost advice

"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."

More Vertica pricing and cost advice

See which vendors are best for you

Use our free recommendation engine to learn which Data Warehouse solutions are best for your needs.

See recommendations

844,944 professionals have used our research since 2012.

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

34%

Computer Software Company

11%

University

Energy/Utilities Company

Financial Services Firm

20%

Computer Software Company

18%

Manufacturing Company

Real Estate/Law Firm

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?

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...

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 22% of the time

Azure Data Factory vs Apache Hadoop

Compared 13% of the time

Teradata vs Apache Hadoop

Compared 13% of the time

BigQuery vs Apache Hadoop

Compared 10% of the time

Databricks vs Apache Hadoop

Compared 4% of the time

More Apache Hadoop Competitors

SQL Server vs Vertica

Compared 14% of the time

Teradata vs Vertica

Compared 12% of the time

Snowflake vs Vertica

Compared 11% of the time

BigQuery vs Vertica

Compared 9% of the time

Microsoft Azure Synapse Analytics vs Vertica

Compared 2% of the time

More Vertica Competitors

Product Reports

Buyer's Guide

Apache Hadoop

March 2025

Download Apache Hadoop product report

Buyer's Guide

Vertica

March 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

February 2025

Free Report: Apache Hadoop vs. Vertica

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

DOWNLOAD NOW

844,944 professionals have used our research since 2012.

See our Apache Hadoop vs. Vertica report.

See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.

We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.