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Apache Hadoop vs Vertica comparison

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Buyer's Guide
Apache Hadoop vs. Vertica
July 2022
Find out what your peers are saying about Apache Hadoop vs. Vertica and other solutions. Updated: July 2022.
610,229 professionals have used our research since 2012.
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"The performance is pretty good.""The scalability of Apache Hadoop is very good.""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 designed to be scalable, so I don't think that it has limitations in regards to scalability.""We selected Apache Hadoop because it is not dependent on third-party vendors.""Hadoop is extensible — it's elastic."

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"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.""Allows us to take volumes and process them at a very high speed.""Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data.""The feature I like best is performance. We use Red Tool and Red Job for the data warehouse and reporting. It's perfect. Performance is good, and it can return ad hoc queries very quickly. Of course, it's a cluster, so it's easy to scale.""It's the fastest database I have ever tested. That's the most important feature of Vertica.""The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful.""Speed and resiliency are probably the best parts of this product.""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."

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Cons
"The solution is very expensive.""Hadoop's security could be better.""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.""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.""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."

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"Support is an area where it could get better.""The integration of this solution with ODI could be improved.""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.""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.""They could improve on customer service.""Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint.""I think they need an easy client so that you can write queries easily, but it's not necessarily a weak point. I think some users would need them.""I have found that coding support could be simplified."

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Pricing and Cost Advice
  • "The price of Apache Hadoop could be less expensive."
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  • "From a cost perspective, the software is less than most of its competitors."
  • "It's difficult today to compete with open-source solutions. In these areas, there is a lot of competition and the price of this solution is a bit pricy."
  • "The price could be cheaper and it is best to negotiate the price."
  • "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."
  • "The pricing could improve, it is a little expensive."
  • "The pricing depends on the license model because there are several. It depends on the client, but it's cheaper than other solutions. I think it's cheap for all the functionality and robustness. It's not very expensive to deploy."
  • "The pricing for this solution is very reasonable compared to other vendors."
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    Questions from the Community
    Top Answer:I don't think using Apache Spark without Hadoop has any major drawbacks or issues. I have used Apache Spark quite successfully with AWS S3 on many projects which are batch based. Yes for very high… more »
    Top Answer:The scalability of Apache Hadoop is very good.
    Top Answer: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.
    Top Answer:The pricing for this solution is very reasonable compared to other vendors.
    Top Answer:The integration of this solution with ODI could be improved.
    Ranking
    5th
    out of 30 in Data Warehouse
    Views
    6,020
    Comparisons
    5,247
    Reviews
    6
    Average Words per Review
    446
    Rating
    7.7
    4th
    out of 30 in Data Warehouse
    Views
    8,892
    Comparisons
    6,868
    Reviews
    9
    Average Words per Review
    511
    Rating
    9.0
    Comparisons
    Also Known As
    Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand
    Learn More
    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.

    Micro Focus Vertica is the most advanced SQL database analytics portfolio built from the very first line of code to address the most demanding Big Data analytics initiatives. Micro Focus Vertica delivers speed without compromise, scale without limits, and the broadest range of consumption models. Choose Vertica on premise, on demand, in the cloud, or on Hadoop. With support for all leading BI and visualization tools, open source technologies like Hadoop and R, and built-in analytical functions, Vertica helps you derive more value from your Enterprise Data Warehouse and data lakes and get to market faster with your analytics initiatives.

    To learn more about Micro Focus Vertica Advanced Analytics, visit our website.

    Offer
    Learn more about Apache Hadoop
    Learn more about Vertica
    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.
    Top Industries
    REVIEWERS
    Financial Services Firm50%
    Comms Service Provider25%
    Consumer Goods Company13%
    Government13%
    VISITORS READING REVIEWS
    Computer Software Company25%
    Comms Service Provider16%
    Financial Services Firm15%
    Energy/Utilities Company5%
    REVIEWERS
    Computer Software Company21%
    Media Company18%
    Marketing Services Firm15%
    Comms Service Provider12%
    VISITORS READING REVIEWS
    Computer Software Company28%
    Comms Service Provider18%
    Financial Services Firm9%
    Manufacturing Company5%
    Company Size
    REVIEWERS
    Small Business36%
    Midsize Enterprise27%
    Large Enterprise36%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise14%
    Large Enterprise71%
    REVIEWERS
    Small Business33%
    Midsize Enterprise26%
    Large Enterprise41%
    VISITORS READING REVIEWS
    Small Business15%
    Midsize Enterprise15%
    Large Enterprise70%
    Buyer's Guide
    Apache Hadoop vs. Vertica
    July 2022
    Find out what your peers are saying about Apache Hadoop vs. Vertica and other solutions. Updated: July 2022.
    610,229 professionals have used our research since 2012.

    Apache Hadoop is ranked 5th in Data Warehouse with 6 reviews while Vertica is ranked 4th in Data Warehouse with 12 reviews. Apache Hadoop is rated 7.6, while Vertica is rated 9.0. The top reviewer of Apache Hadoop writes "Great micro-partitions, helpful technical support and quite stable". On the other hand, the top reviewer of Vertica writes "Superior performance in speed and resilience makes this a very good warehousing solution". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Snowflake, Oracle Exadata, VMware Tanzu Greenplum and Oracle Big Data Appliance, whereas Vertica is most compared with Snowflake, Teradata, Amazon Redshift, SQL Server and Microsoft Azure Synapse Analytics. See our Apache Hadoop vs. Vertica report.

    See our list of best 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.