OpenText Analytics Database (Vertica) vs Treasure Data comparison

OpenText and Treasure Data are both solutions in the Data Warehouse category. OpenText is ranked #5 with an average rating of 8.3, while Treasure Data is ranked #17 with an average rating of 9.0. OpenText holds a 5.7% mindshare in Data Warehouse, compared to Treasure Data’s 1.6% mindshare. Additionally, 91% of OpenText users are willing to recommend the solution, compared to 100% of Treasure Data users who would recommend it.

OpenText Analytics Database...

Read 90 OpenText Analytics Database (Vertica) reviews

6,620 Views
3,442 Comparison Views

91% willing to recommend

Treasure Data

Read 1 Treasure Data review

1,216 Views
462 Comparison Views

100% willing to recommend

OpenText Analytics Database...

Treasure Data

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Executive SummaryUpdated on Mar 29, 2026

OpenText Analytics Database Vertica and Treasure Data are competitors in the analytics database market due to their capabilities in handling large data sets and performing advanced analytics. Treasure Data seems to have the upper hand thanks to its extensive integration capabilities and flexibility, offering a comprehensive solution with justifiable costs.

Features: OpenText Analytics Database Vertica leverages columnar storage, high-speed queries, and robust data compression for efficient complex analytics. Treasure Data provides powerful data integration features, real-time streaming, and an emphasis on ease of use through simplified workflows.

Ease of Deployment and Customer Service: OpenText Analytics Database Vertica offers seamless deployment options with strong technical support targeting enterprises in need of reliable infrastructure. Treasure Data provides cloud-based deployment and intuitive onboarding, focusing on quick setup and minimal infrastructure management.

Pricing and ROI: OpenText Analytics Database Vertica features competitive pricing with high ROI for high-performance analytics environments. Treasure Data's pricing reflects its comprehensive features and flexibility, offering value to businesses seeking flexible pricing models.

To learn more, read our detailed Data Warehouse Report (Updated: May 2026).

Buyer's Guide

Data Warehouse

May 2026

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Helped 893,164 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

OpenText Analytics Database...

Ranking in Data Warehouse

5th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (11th)

Treasure Data

Ranking in Data Warehouse

17th

Average Rating

9.0

Reviews Sentiment

5.8

Number of Reviews

Ranking in other categories

Customer Data Platforms (CDP) (3rd), AI Customer Experience Personalization (39th)

Mindshare comparison

As of May 2026, in the Data Warehouse category, the mindshare of OpenText Analytics Database (Vertica) is 5.7%, down from 8.4% compared to the previous year. The mindshare of Treasure Data is 1.6%, up from 0.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
OpenText Analytics Database (Vertica)	5.7%
Treasure Data	1.6%
Other	92.7%

Data Warehouse

Featured Reviews

Jitendrak Naik

consultant at tcs

Data warehousing has transformed reporting performance and now delivers near real-time insights

OpenText Analytics Database (Vertica) is a very powerful analytic database, but like any platform, there are areas where it can improve to make daily work even smoother. Better cloud-native experience is one area for improvement. OpenText Analytics Database (Vertica) was originally designed as an on-premises analytic database and later moved to cloud. Improvement opportunities include more seamless cloud-native features such as auto-scaling, serverless options, and easier cluster management. Competitors such as Snowflake and BigQuery provide more fully managed experiences. Easier UI is another area for improvement. Most administration is currently done by SQL and command line tools. An improvement opportunity would be a more modern web UI for monitoring, workload management, and troubleshooting. Faster ecosystem and community growth is needed. In short, OpenText Analytics Database (Vertica) could improve in areas such as cloud-native capability, modern UI for administration, stronger real-time streaming integration, and growing its ecosystem and community. These enhancements would make it easier to manage and adopt compared to newer cloud-first analytic platforms. From a day-to-day operational perspective, there are a few areas where OpenText Analytics Database (Vertica) could improve to make our work smoother. Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management. Right now, monitoring queries often requires system tables and manual analysis. Troubleshooting slow queries takes time. A modern real-time dashboard showing query bottlenecks and resource users would enable quick detection. The impact could be faster issue resolution and less time spent debugging performance. Storage native interaction with modern data tools is also important. In short, from a day-to-day perspective, improvements in automatic projection optimization, better workload monitoring dashboard, easier schema evolution, and stronger modern tool integration would significantly reduce manual tuning effort and improve developer productivity. While OpenText Analytics Database (Vertica) is very powerful, these enhancements would make it more efficient for the analytics team.

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DEEPAK SINGH THAKUR

Software Engineer at Indegene

Users can effortlessly create tables and manage data, even without utilizing the graphical interface

The initial setup is difficult due to the lack of detailed documentation. While the documentation provides a high-level overview, it lacks the specific instructions needed for setup. We relied on assistance from the Treasure Data team, including their support team, to navigate the process. Additionally, various policies to consider further complicate the setup, which ultimately requires time. We handle a large volume of data, and ensuring everything runs smoothly is crucial. Previously, it would take three to four months for one deployment due to the need to create workflows, conduct functional and comprehensive testing to ensure everything works seamlessly, and then proceed with delivery.

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Top Industries

By visitors reading reviews

Financial Services Firm

18%

Computer Software Company

12%

Manufacturing Company

Comms Service Provider

Construction Company

15%

Manufacturing Company

15%

Computer Software Company

Recreational Facilities/Services Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	29
Midsize Enterprise	23
Large Enterprise	43

No data available

Questions from the Community

What do you like most about Vertica?

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

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What is your experience regarding pricing and costs for Vertica?

My experience with pricing, setup cost, and licensing is limited because the organization handled the licensing and pricing as well as the cost setup.

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What needs improvement with Vertica?

OpenText Analytics Database (Vertica) is already doing great. There could be a community which could have been much more advanced and more people can be engaged so that any kind of questions, queri...

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What needs improvement with Treasure Data?

In data management, we have a lot of data, including some PII, visible to everyone without any restrictions. This poses a significant problem because there isn't proper control over who can access ...

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What is your primary use case for Treasure Data?

We need to create a 360-degree profile of a user using data from multiple sources. Subsequently, we utilize this data for marketing purposes.

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What advice do you have for others considering Treasure Data?

We used to gather data from various sources, including websites. The data used to flow in real-time, requiring us to capture it promptly. Within seconds, we could see four to five reports. Treasure...

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Comparisons

Teradata vs OpenText Analytics Database (Vertica)

Compared 7% of the time

Snowflake vs OpenText Analytics Database (Vertica)

Compared 7% of the time

Oracle Exadata vs OpenText Analytics Database (Vertica)

Compared 5% of the time

SAP IQ vs OpenText Analytics Database (Vertica)

Compared 4% of the time

SQL Server vs OpenText Analytics Database (Vertica)

Compared 4% of the time

More OpenText Analytics Database (Vertica) Competitors

Amperity vs Treasure Data

Compared 17% of the time

Teradata vs Treasure Data

Compared 13% of the time

Hightouch vs Treasure Data

Compared 11% of the time

mParticle vs Treasure Data

Compared 10% of the time

SAP IQ vs Treasure Data

Compared 4% of the time

More Treasure Data Competitors

Product Reports

Buyer's Guide

OpenText Analytics Database (Vertica)

April 2026

OpenText Analytics Database (Vertica) report

Download OpenText Analytics Database (Vertica) product report

Buyer's Guide

Customer Data Platforms (CDP)

May 2026

Download Treasure Data product report

Also Known As

Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand

No data available

Overview

OpenText Analytics Database Vertica is known for its fast data loading and efficient query processing, providing scalability and user-friendliness with a low cost per TB. It supports large data volumes with OLAP, clustering, and parallel ingestion capabilities.

OpenText Analytics Database Vertica is designed to handle substantial data volumes with a focus on speed and efficient storage through its columnar architecture. It offers advanced performance features like workload isolation and compression, ensuring flexibility and high availability. The database is optimized for scalable data management, supporting data scientists and analysts with real-time reporting and analytics. Its architecture is built to facilitate hybrid deployments on-premises or within cloud environments, integrating seamlessly with business intelligence tools like Tableau. However, challenges such as improved transactional capabilities, optimized delete processes, and better real-time loading need addressing.

What features define OpenText Analytics Database Vertica?

Fast Data Loading: Quickly ingests large data volumes.
Columnar Storage: Optimizes storage efficiency and speed.
OLAP Support: Provides robust analytics capabilities.
Advanced Compression: Enhances storage efficiency and performance.
Parallel Data Ingestion: Enables faster data processing.
Fault Tolerance: Ensures high availability and reliability.

What benefits should users expect?

Cost Efficiency: Low cost per TB is advantageous.
Scalability: Accommodates growing data needs seamlessly.
Integration Flexibility: Works well with BI tools like Tableau.
Real-Time Reporting: Delivers immediate insights for decision-making.

OpenText Analytics Database Vertica's implementation spans industries such as finance, healthcare, and telecommunications. It serves as a central data warehouse offering scalable management, high-speed processing, and geospatial functions. Companies benefit from its capacity to integrate machine learning and operational reporting, enhancing analytical capabilities.

OpenText

Treasure Data offers a powerful data management platform primarily used for customer data integration and behavior analytics. It excels in creating unified views of customer data from multiple sources, enabling tailored marketing and optimized targeted advertising through robust segmentation and predictive analytics. With a user-friendly interface and real-time analytics, it enhances organizational efficiency, supports large-scale data processing, and aids in making quick, informed decisions.

Treasure Data

Sample Customers

Cerner, Game Show Network Game, Guess by Marciano, Supercell, Etsy, Nascar, Empirix, adMarketplace, and Cardlytics.

Pioneer, Dentsu, Diverse, Albert, Retty, FreakOut, Mobfox, Pebble, Livesense, GREE, Cookpad, Dashbid, Cloud9, Just Premium

Find out what your peers are saying about Snowflake Computing, Oracle, Teradata and others in Data Warehouse. Updated: May 2026.

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