Apache Hadoop vs Vertica comparison

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Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Hadoop and Vertica based on real PeerSpot user reviews.

Find out in this report how the two Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Apache Hadoop vs. Vertica Report (Updated: March 2024).
763,955 professionals have used our research since 2012.
Q&A Highlights
Question: Which is the best RDMBS solution for big data?
Answer: 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
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"It's open-source, so it's very cost-effective.""The most valuable features are powerful tools for ingestion, as data is in multiple systems.""The ability to add multiple nodes without any restriction is the solution's most valuable aspect.""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.""​​Data ingestion: It has rapid speed, if Apache Accumulo is used.""The performance is pretty good.""We selected Apache Hadoop because it is not dependent on third-party vendors.""Apache Hadoop can manage large amounts and volumes of data with relative ease, which is a feature that is beneficial."

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"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance.""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 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.""We are also opening new areas of business and potential new revenue streams using Vertica's analytic functions, most notably geospatial, where we are able to run billions of comparisons of lat/long point locations against polygon and point/radius locations in seconds. ​""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.""DBAs don’t need to add a partition every month/quarter like with other DBs.""I don't need any special hardware. I can use commodity hardware, which is nice to have in a commercial solution.""Vertica is a columnar database, this support our developments in analytics, advanced analytics, and ETL process with large sets of data."

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Cons
"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.""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.""It needs better user interface (UI) functionalities.""The solution is very expensive.""It would be good to have more advanced analytics tools.""It would be helpful to have more information on how to best apply this solution to smaller organizations, with less data, and grow the data lake.""General installation/dependency issues were there, but were not a major, complex issue. While migrating data from MySQL to Hive, things are a little challenging, but we were able to get through that with support from forums and a little trial and error.""We would like to have more dynamics in merging this machine data with other internal data to make more meaning out of it."

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"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.""The integration with AI has room for improvement.""The biggest problem is the cost of cloud deployment.""Suboptimal projection design causes queries to not scale linearly.""They could improve the integration and some of the features in the cloud version.""If you do not utilize the tuning tools like projections, encoding, partitions, and statistics, then performance and scalability will suffer.""The integration of this solution with ODI could be improved.""When it is about to reach the maximum storage capacity, it becomes slow."

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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."
  • "​There are no licensing costs involved, hence money is saved on the software infrastructure​."
  • "This is a low cost and powerful solution."
  • "The price of Apache Hadoop could be less expensive."
  • "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 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 price could be better. Hortonworks no longer exists, and Cloudera killed the free version of Hadoop."
  • "We just use the free version."
  • More Apache Hadoop Pricing and Cost Advice →

  • "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 free up to three nodes and 1TB, and then get in contact with their sales guys."
  • "Start with license per 1TB. Starting from hundreds of TB there is unlimited licensing to be considered. Move historical data to HDFS/S3 which are significantly cheaper or even free."
  • "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."
  • "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."
  • "Read the fine print carefully."
  • "It is fast to purchase through the AWS Marketplace."
  • "The pricing and licensing depend on the size of your environment and the zone where you want to implement."
  • More Vertica Pricing and Cost Advice →

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    Answers from the Community
    Anonymous User
    Yuval Klein - PeerSpot reviewerYuval Klein
    Real User

    SQreamDB is a GPU DB. It is not suitable for real-time oltp of course.

    Cassandra is best suited for OLTP database use cases, when you need a scalable database (instead of SQL server, Postgres)
    SQream is a GPU database suited for OLAP purposes. It's the best suite for a very large data warehouse, very large queries needed mass parallel activity since GPU is great in massive parallel workload.

    Also, SQream is quite cheap since we need only one server with a GPU card, the best GPU card the better since we will have more CPU activity. It's only for a very big data warehouse, not for small ones.

    Tristan Bergh - PeerSpot reviewerTristan Bergh
    Real User

    Your best DB for 40+ TB is Apache Spark, Drill and the Hadoop stack, in the cloud.

    Use the public cloud provider's elastic store (S3, Azure BLOB, google drive) and then stand up Apache Spark on a cluster sized to run your queries within 20 minutes. Based on my experience (Azure BLOB store, Databricks, PySpark) you may need around 500 32GB nodes for reading 40 TB of data.

    Costs can be contained by running your own clusters but Databricks manage clusters for you.

    I would recommend optimizing your 40TB data store into the Databricks delta format after an initial parse.

    Russell Rothstein - PeerSpot reviewerRussell Rothstein (PeerSpot)
    Vendor

    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.

    Questions from the Community
    Top Answer:It's open-source, so it's very cost-effective.
    Top Answer:The main thing is the lack of community support. If you want to implement a new API or create a new file system, you won't find easy support. And then there's the server issue. You have to create and… more »
    Top Answer:The product's initial setup phase is extremely simple.
    Top Answer:In my opinion, nothing needs improvement in the solution as it is a great product. The documentation of Vertica is an area with shortcomings where improvements are required. Vertica needs to increase… more »
    Ranking
    5th
    out of 33 in Data Warehouse
    Views
    2,765
    Comparisons
    2,378
    Reviews
    10
    Average Words per Review
    539
    Rating
    8.0
    4th
    out of 33 in Data Warehouse
    Views
    4,414
    Comparisons
    3,480
    Reviews
    10
    Average Words per Review
    353
    Rating
    8.3
    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.

    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

    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 Firm40%
    Comms Service Provider27%
    Hospitality Company7%
    Consumer Goods Company7%
    VISITORS READING REVIEWS
    Financial Services Firm27%
    Computer Software Company10%
    Comms Service Provider6%
    Educational Organization6%
    REVIEWERS
    Computer Software Company20%
    Media Company17%
    Marketing Services Firm14%
    Comms Service Provider11%
    VISITORS READING REVIEWS
    Financial Services Firm18%
    Computer Software Company15%
    Manufacturing Company8%
    Comms Service Provider6%
    Company Size
    REVIEWERS
    Small Business33%
    Midsize Enterprise24%
    Large Enterprise42%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise10%
    Large Enterprise75%
    REVIEWERS
    Small Business31%
    Midsize Enterprise27%
    Large Enterprise42%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise13%
    Large Enterprise67%
    Buyer's Guide
    Apache Hadoop vs. Vertica
    March 2024
    Find out what your peers are saying about Apache Hadoop vs. Vertica and other solutions. Updated: March 2024.
    763,955 professionals have used our research since 2012.

    Apache Hadoop is ranked 5th in Data Warehouse with 11 reviews while Vertica is ranked 4th in Data Warehouse with 10 reviews. Apache Hadoop is rated 7.8, while Vertica is rated 8.4. The top reviewer of Apache Hadoop writes "Has good processing power and speed and is capable of handling large volumes of data and doing online analysis". On the other hand, the top reviewer of Vertica writes "Reliable and feature-rich, with optimization techniques to fine-tune queries for faster report generation". Apache Hadoop is most compared with Microsoft Azure Synapse Analytics, Azure Data Factory, Oracle Exadata, Snowflake and Oracle Big Data Appliance, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and SingleStore. 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.