Overview
What is OpenText Vertica?
The Vertica Analytics Platform supplies enterprise data warehouses with big data analytics capabilities and modernization. Vertica is owned and supported by OpenText.
Good analytical database
Robust Vertica Experience
Vertica Review
Analysis at Scale
Fast with some limitations
Vertica's Strengths and Weakness
Fast and powerful analytics platform
Pricing
What is OpenText Vertica?
The Vertica Analytics Platform supplies enterprise data warehouses with big data analytics capabilities and modernization. Vertica is owned and supported by OpenText.
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- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Demos
Vertica in-DB Machine Learning Demo
How to recover a HP Vertica Database Node from a Corrupted Catalog
Vertica Optimized for Multiple Clouds Using Attunity Replicate
vertica and elastic search demo
WEBINAR: Predictive Analytics with Vertica
Utilizing Tableau and HP Vertica Demo - Consolidating Worksheets into a Single Dashboard
Product Details
- About
- Tech Details
What is OpenText Vertica?
OpenText Vertica Video
OpenText Vertica Technical Details
Operating Systems | Unspecified |
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Mobile Application | No |
Comparisons
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Reviews and Ratings
(29)Community Insights
- Business Problems Solved
- Pros
- Cons
- Recommendations
Vertica has become a crucial tool for businesses looking to analyze large volumes of data for various use cases. Users have found it particularly valuable as a data warehouse for analyzing internal business data and marketing results of clients. Its ability to handle large data sizes enables analysis at a level that would not have been possible otherwise. Uber, for example, has successfully employed Vertica for their data analytics needs. Additionally, companies have created Vertica-based data marts to provide analytics insights and support data science across their entire organizations.
One key advantage of Vertica is its complementary nature with other technologies like Hadoop. By leveraging its high scale capabilities, Vertica enhances data efforts when used alongside Hadoop. The software also serves as the main data warehouse, acting as a source for analytic reports and facilitating data analysis activities. Interestingly, users have discovered non-traditional applications for Vertica, utilizing it as a powerful data processing engine to solve problems at scale. For instance, in the entertainment industry, Vertica is instrumental in rendering data and performing big data analysis tasks efficiently.
The speed of Vertica is highly beneficial to users, allowing them to quickly complete ad-hoc queries and conduct more in-depth analyses. This speed sets Vertica apart from competitors in the highly ingested, fast query analytics niche, including platforms like Teradata, Greenplum, Exadata, and Netezza. Moreover, Vertica excels in handling large amounts of data ingestion quickly, making it a reliable tool for organizations dealing with vast quantities of information.
Furthermore, Vertica serves as an analytics database that can handle real-time streaming data from sources like Apache Kafka. This capability enables organizations to gain near real-time customer insights for their consumer-facing web portals and mobile applications. Overall, users have come to rely on Vertica as an essential analytics database for reporting, ad-hoc queries, and more in-depth analyses across a wide range of industries and use cases.
Impressive Analytical Querying Capabilities: Several reviewers have praised Vertica for its impressive analytical querying capabilities. Users have found the built-in analytical functions to be powerful, allowing them to perform complex analyses across terabytes of data. This feature has enabled users to gain interesting insights and make data-driven decisions.
Efficient Data Ingestion: Many users have highlighted Vertica's efficient data ingestion process as a major advantage. According to reviewers, billions of rows can be easily sent to Vertica via the WOS system, and the data is ready for immediate use. This streamlined data ingestion process not only saves time but also enables quick analysis, enhancing productivity.
Scalability and Performance: The scalability and performance of Vertica have been widely appreciated by reviewers. Users have mentioned that Vertica can scale reasonably well up to 10-20 nodes and handle hundreds of terabytes of data effectively. Additionally, many reviewers consider Vertica as one of the fastest query engines available, with tables containing billions of rows still delivering speedy results for analytical tasks.
Deletion Process: Users have expressed frustration with the deletion process in Vertica, stating that it does not fully delete when prompted and can cause delays in other processes. Some users have reported this issue.
Permissions on Table Manipulation: Reviewers find the permissions on table manipulation lacking in Vertica, as only the owner of the table can edit its structure. This makes it difficult to set up true administrators who can maintain each other's work. Several users have mentioned this limitation.
Handling Petabyte-Scale Data: Vertica struggles to handle petabyte-scale data according to user feedback. It starts to crumble beyond hundreds of terabytes of data. Numerous reviewers have noted this scalability issue.
Users have made several recommendations based on their experience with Vertica. The most common recommendations are:
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Proper Testing and Preparation: Users suggest that before releasing a major version of Vertica, it is crucial to have thorough testing in place. This ensures that any potential issues or bugs are identified and resolved prior to deployment.
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Follow Vendor Configuration Instructions: It is advised to closely follow the vendor's configuration instructions when setting up Vertica. This helps ensure optimal performance and stability of the tool.
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Training and Familiarity: Users recommend sending database administrators (DBAs) for training and studying the SQL limitations of Vertica. It is important to have a good understanding of Vertica and its capabilities to effectively leverage the tool for solving specific business problems.
It is important to note that while Vertica is highly recommended for data warehousing, solving Big Data solutions, and analytical data warehousing, users also suggest considering other database systems if there is not a significant amount of data that needs to be accessed quickly or if a more common/easier-to-set-up system would suffice.
Attribute Ratings
Reviews
(1-7 of 7)Good analytical database
Robust Vertica Experience
Vertica Review
Analysis at Scale
Fast with some limitations
Vertica's Strengths and Weakness
Scaling for PB data and 1000s of DAU is vertica's weak point. The system is just not designed for large scale usage and still has a long way to go to improve scalability. There are experiments to run Vertica query engine on top of HDFS which seem promising, however - if you have the the Hadoop ecosystem you are better off going the HDFS + Presto/Impala/SparkSQL route. But if you are in the Hadoop ecosystem, you probably are already investing a lot in ops.
Fast and powerful analytics platform
Vertica is not the silver bullet but based on my experience in 9/10 cases in which you need an analytical database, Vertica is probably the answer.
Currently we're using Vertica more as a data processing engine in conjunction with a Hadoop cluster as some of the steps are way more efficient than doing them in Hadoop and easier to manage (e.g. iterative processing steps). We also had a pretty good experience using it with Storm and Hadoop.