OpenText Analytics Database (Vertica) vs Redis comparison

OpenText Analytics Database...

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Executive Summary

We performed a comparison between OpenText Analytics Database (Vertica) and Redis based on real PeerSpot user reviews.

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NoSQL Databases

September 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

ROI

Sentiment score

6.2

Organizations achieved financial and operational gains with Vertica, reducing costs and processing time while enhancing analytics and performance.

Sentiment score

7.3

Redis boosts performance and reduces costs, enhancing API latency and productivity while allowing focus on feature development.

I saved a lot of money because the storage was on a cheaper alternative and was not directly on OpenText Analytics Database (Vertica), but on S3.

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

The time we used to take with our earlier databases has reduced to one-tenth of what was there earlier, which is a positive outcome that can be converted to financial metrics in terms of return on investment.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Data Engineering Associate Manager at a tech vendor with 10,001+ employees

We reduced the database read load by around 30 to 40 percent and improved API response time by 20 to 30 percent, specifically for frequently accessed endpoints.

SDE 2 at Virtusa

We have seen a positive return on investment from using Redis, mainly through improved application performance, reduced database load, and lower operational overhead.

For more quotes and insights, download the Redis report

Senior Software Engineer at a consultancy with 1-10 employees

Customer Service

Sentiment score

7.1

OpenText Analytics Database's customer service is generally valued for expertise but has occasional response time and escalation issues.

Sentiment score

6.4

Redis users rarely need support due to stability, relying on documentation and community, with mixed experiences reported.

Throughout this process, customer support was outstanding, and we had a person actively supporting us from the OpenText Analytics Database (Vertica) team for our use case.

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

Overall, our experience with OpenText Analytics Database (Vertica) customer support has been good and reliable.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

consultant at tcs

By simply referring to their documentation, we have been able to fix our bugs and general issues.

Senior Software Engineer at a consultancy with 1-10 employees

Since Redis is quite stable and well-documented, we have not needed much support, but when required, the response has been helpful.

For more quotes and insights, download the Redis report

SDE 2 at Virtusa

Scalability Issues

Sentiment score

7.2

OpenText Vertica offers scalable, efficient data handling with robust performance, though pricing and node addition may challenge some users.

Sentiment score

7.8

Redis excels in scalability and efficiency, handling high traffic with clustering and sharding, benefiting enterprise application demands.

We have experienced easy horizontal scaling, consistent query performance as data grew, and the ability to handle large analytic workloads.

consultant at tcs

OpenText Analytics Database (Vertica) has very good scalability.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Data Engineering Associate Manager at a tech vendor with 10,001+ employees

OpenText Analytics Database (Vertica) can scale to a great extent.

Anuj Chourasia

Analytics Manager at a wholesaler/distributor with 10,001+ employees

The in-memory architecture provides consistently low-latency access even as data access patterns and request volume increase.

Senior Software Engineer at a consultancy with 1-10 employees

Data migration and changes to application-side configurations are challenging due to the lack of automatic migration tools in a non-clustered legacy system.

Data Engineer at a photography company with 1,001-5,000 employees

With features such as clustering and replication, it can handle high traffic and a large database very effectively.

For more quotes and insights, download the Redis report

SDE 2 at Virtusa

Stability Issues

Sentiment score

7.2

OpenText Analytics Database offers high stability and performance, with successful migrations and minimal clustering issues ensuring user satisfaction.

Sentiment score

7.9

Redis is lauded for its stability, reliable caching performance, and robust architecture, supported by strong community and managed services.

OpenText Analytics Database (Vertica) is very stable.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

Redis has consistently provided fast and predictable performance, particularly for caching and high-frequency data access scenarios.

Senior Software Engineer at a consultancy with 1-10 employees

Redis is fairly stable.

For more quotes and insights, download the Redis report

Data Engineer at a photography company with 1,001-5,000 employees

Room For Improvement

OpenText Analytics Database needs improvements in community, cloud features, SQL, integration, cost efficiency, machine learning, and developer tools.

Redis users seek improvements in cache management, user interface, observability, scalability, security setup, and cloud integrations for enhanced usability.

Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management.

consultant at tcs

Projections could be made more dynamic, and if they could find a faster way to update, insert, and delete data, that would also be helpful.

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

OpenText Analytics Database (Vertica) does not have a cloud-based UI that Snowflake has, which features a very good comprehensive GUI for querying and analyzing data.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Data Engineering Associate Manager at a tech vendor with 10,001+ employees

Making security features and enterprise governance capabilities easier to configure out of the box would help organizations adopt Redis more confidently for larger and more critical workloads.

Senior Software Engineer at a consultancy with 1-10 employees

Data persistence and recovery face issues with compatibility across major versions, making upgrades possible but downgrades not active.

Data Engineer at a photography company with 1,001-5,000 employees

Redis is very reliable, but it could be improved in areas such as monitoring, debugging, and feasibility into memory use.

For more quotes and insights, download the Redis report

SDE 2 at Virtusa

Setup Cost

OpenText Analytics Database offers flexible pricing, often cost-effective for its advanced features, despite being pricey vs. open-source solutions.

Enterprise Redis costs vary by deployment model, with self-managed being cost-effective and cloud services charging for memory usage.

The pricing for OpenText Analytics Database (Vertica) is somewhat on the higher side for the license.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

The main value comes from the performance improvements, reduced database load, and increased scalability that Redis provides.

Senior Software Engineer at a consultancy with 1-10 employees

Since we use an open-source version of Redis, we do not experience any setup costs or licensing expenses.

Data Engineer at a photography company with 1,001-5,000 employees

The pricing is reasonable for the performance provided.

For more quotes and insights, download the Redis report

SDE 2 at Virtusa

Valuable Features

OpenText Analytics Database excels in fast query responses, scalability, and real-time insights, enhancing decision-making and operational efficiency.

Redis is preferred for speed and reliability, offering low latency, high throughput, and efficient scaling with minimal configuration.

I can use it in Eon Mode in which I can store the data in cheaper storage such as Amazon S3 and have different compute nodes.

Senior Software Engineer at a tech vendor with 5,001-10,000 employees

Projection and columnar storage are the most valuable features because they dramatically improve query performance and reduce the need for index management.

consultant at tcs

The best features that OpenText Analytics Database (Vertica) offers are mainly the parallel processing, ETL capabilities, and the multi-cloud features which are very handy to use.

For more quotes and insights, download the OpenText Analytics Database (Vertica) report

Data Engineering Associate Manager at a tech vendor with 10,001+ employees

It functions similarly to a foundational building block in a larger system, enabling native integration and high functionality in core data processes.

Data Engineer at a photography company with 1,001-5,000 employees

By offloading frequent reads from the database and enabling fast in-memory cache access, it reduced latency, improved throughput, and helped maintain stability during peak loads.

SDE 2 at Virtusa

The most valuable features include high-speed in-memory data access, flexible data structures, caching capabilities, data expiration and time-to-live management, high availability and scalability, and atomic operations.

For more quotes and insights, download the Redis report

Senior Software Engineer at a consultancy with 1-10 employees

Categories and Ranking

OpenText Analytics Database...

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Warehouse (6th), Cloud Data Warehouse (11th)

Redis

Average Rating

8.8

Reviews Sentiment

6.6

Number of Reviews

Ranking in other categories

NoSQL Databases (3rd), Managed NoSQL Databases (5th), In-Memory Data Store Services (1st), Vector Databases (5th), AI Software Development (8th)

Featured Reviews

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

consultant at tcs

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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Caching has improved response times and reduces database load for high-traffic applications

SDE 2 at Virtusa

Redis is very reliable, but it could be improved in areas such as monitoring, debugging, and feasibility into memory use. Better built-in tools for observability would help teams manage it more effectively at scale. Managing memory efficiently and troubleshooting issues can sometimes require additional tooling, so these areas can also be improved.One practical challenge I experienced is managing memory efficiently. Since Redis is in-memory, we need to carefully configure eviction policies and monitor usage. Debugging cache-related issues such as stale data or cache invalidation can sometimes be tricky. Additionally, tuning memory usage and eviction policies needs to be planned very carefully.

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Outsourcing Company

14%

Manufacturing Company

10%

Comms Service Provider

Financial Services Firm

22%

Computer Software Company

Comms Service Provider

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

By reviewers
Company Size	Count
Small Business	13
Midsize Enterprise	6
Large Enterprise	10

Questions from the Community

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.

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...

What is your primary use case for Vertica?

The main use case for OpenText Analytics Database (Vertica) is that we have the Hive and a Hadoop layer for data availability, and Vertica serves as a big data solution. Within a Hive table, OpenTe...

What needs improvement with Redis?

Making management easier, especially for teams operating large Redis clusters, would be helpful. More advanced built-in observability, performance insights, and automated recommendations would help...

What is your primary use case for Redis?

Redis is used primarily as a caching layer to provide a high-performance caching solution that improves application response times and reduces load on backend services and databases. We use it main...

What advice do you have for others considering Redis?

There are a couple of things to consider when using Redis. It is a supporting layer, not a main database. Identifying specific use cases where Redis can provide the most value, such as caching, ses...

Teradata vs OpenText Analytics Database (Vertica)

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Product Reports

Buyer's Guide

OpenText Analytics Database (Vertica)

September 2026

OpenText Analytics Database (Vertica) report

Download OpenText Analytics Database (Vertica) product report

Buyer's Guide

Download Redis product report

September 2026

Also Known As

Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand

Redis Enterprise

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

Redis offers high-speed, in-memory storage, renowned for real-time performance. It supports quick data retrieval and is used commonly in applications like analytics and gaming.

Renowned for real-time performance, Redis delivers high-speed in-memory storage, making it a favorite for applications needing quick data retrieval. Its diverse data structures and caching capabilities support a broad array of use cases, including analytics and gaming. Redis ensures robust scalability with master-slave replication and clustering, while its publish/subscribe pattern renders it reliable for event-driven applications. The solution integrates smoothly with existing systems, minimizing performance tuning needs. Although documentation on scalability and security could be improved, Redis remains cost-effective and stable, commonly utilized in cloud environments. Enhancing integration with cloud services like AWS and Google Cloud and refining GUI may improve usability.

What are the key features of Redis?

High Speed: In-memory data storage for swift access.
Scalability: Master-slave replication and clustering for growth.
Data Structures: Supports diverse types for varied uses.
Persistence: RDB snapshots and AOF logs ensure durability.
Integration: Seamless integration reduces tuning efforts.

What should users look for in Redis reviews?

Performance: Real-time data retrieval boosts efficiency.
Cost-Effectiveness: Stable, budget-friendly implementation.
Versatility: Suitable for diverse environments and platforms.
Reliability: Ensures data persistence and high availability.

Redis finds application across industries for tasks like caching to improve application performance and speed, minimizing database load. It enables real-time processing for session storage, push notifications, and analytics. As a messaging platform, Redis handles high traffic and supports replication and clustering for cross-platform scalability.