Citus Data vs OpenText Analytics Database (Vertica) comparison

Why PeerSpot?

The compared Citus Data and OpenText solutions aren't in the same category. Citus Data is ranked #31 in SQL , and holds a 1.9% mindshare in the category. OpenText is ranked #5 in Data Warehouse , with an average rating of 8.5, and holds a 6.5% mindshare. Additionally, 100% of Citus Data users are willing to recommend the solution, compared to 91% of OpenText users who would recommend it.

Citus Data

Read 3 Citus Data reviews

2,349 Views
2,232 Comparison Views

100% willing to recommend

OpenText Analytics Database...

Read 90 OpenText Analytics Database (Vertica) reviews

10,194 Views
5,913 Comparison Views

91% willing to recommend

Citus Data

OpenText Analytics Database...

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Executive Summary

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

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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:

Categories and Ranking

Citus Data

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

Relational Databases Tools (31st)

OpenText Analytics Database...

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Warehouse (5th), Cloud Data Warehouse (12th)

Mindshare comparison

Citus Data and OpenText Analytics Database (Vertica) aren’t in the same category and serve different purposes. Citus Data is designed for Relational Databases Tools and holds a mindshare of 1.9%, down 2.6% compared to last year.
OpenText Analytics Database (Vertica), on the other hand, focuses on Data Warehouse, holds 6.5% mindshare, up 6.3% since last year.

Relational Databases Tools Mindshare Distribution
Product	Mindshare (%)
Citus Data	1.9%
Oracle Database	10.3%
SQL Server	10.2%
Other	77.6%

Relational Databases Tools

Data Warehouse Mindshare Distribution
Product	Mindshare (%)
OpenText Analytics Database (Vertica)	6.5%
Teradata	9.1%
Snowflake	8.8%
Other	75.6%

Data Warehouse

Featured Reviews

Arucy Lionel

Co-Founder at Afriziki

Efficiently handles high-traffic scenarios and compatible with PostgreSQL extensions, offering flexibility in database management

There are many areas of improvement , especially in terms of DDL query routing. Even though it's masterless, DDL queries need to be sent to the coordinator node. Also, setting up a multi-node environment could be more straightforward. Currently, setting up a multi-node environment is challenging. It's a bit tricky. Installation on each PostgreSQL node can lead to communication issues between nodes. An automatic rebalancing feature would be a significant improvement. Currently, I have to manually command the rebalance. It would be more convenient if it was rebalanced automatically. The dashboard and monitoring capabilities are good, but it would be helpful to have an integrated availability dashboard.

Read full review

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.

Read full review

Quotes from Members

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

Pros

"You can use Citus Data to write complex scripts. I like its version upgrades and disaster recovery as well."

"Its distributed processing capabilities are a standout feature. It requires minimal changes to get up and running if you already have a system on PostgreSQL. Citus can run in its natural state."

"It's very straightforward to implement the solution. It took us two days to set up everything."

"The solution is competitive with Mongo, MySQL, and maybe even Oracle."

"Great product, very mature and robust."

"Vertica is an excellent data warehouse platform."

"Integrated R and geospatial functions are helping us improve efficiency and explore new revenue streams. "

"Vertica stands top among its peers in the MPP world, delivering unparalleled speed and performance in query response time."

"It's the fastest database I have ever tested. That's the most important feature of Vertica."

"Vertica uses advanced Azure technologies to compress raw data using indexing, allowing a large amount of data to be stored with minimal physical space. Advanced algorithms are employed in data compression."

"We are using Vertica because it is a fast and reliable data warehousing tool and provides us a very good data compression ratio."

"The most valuable feature is Vertica's performance and the ease of using the database."

More OpenText Analytics Database (Vertica) pros

Cons

"Citus Data needs to improve its stability. Do not consider this product if you have the budget. It is still developing and has a lot of issues."

"There are many areas of improvement , especially in terms of DDL query routing. Even though it's masterless, DDL queries need to be sent to the coordinator node. Also, setting up a multi-node environment could be more straightforward."

"More features in monitoring and the reporting could make it better."

"Metadata for database files scale okay, but metadata related to tables/columns/sequences must be stored on all nodes."

"The product could be less expensive and could benefit from a better marketing strategy."

"It's hard to make it slow for a small data volume. For large volumes, it's hard to make it work. It's also hard to make it faster, and to make it scale."

"It needs to handle high concurrency short queries better as Vertica is not handling these well, and we have had to develop our own tool to help us with our dashboard."

"I really would like to see Vertica able to use heterogeneous storage (RAM, SSD, HDD). Another issue I have seen is that the SQL optimizer fails to make optimizations that competing products are able to do."

"Suboptimal projection design causes queries to not scale linearly."

"Node recovery is very inconsistent and impacts performance."

"In data streaming ROS containers is a pain to work with."

More OpenText Analytics Database (Vertica) cons

Pricing and Cost Advice

"Citus Data is an open-source product."

"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."

"From a cost perspective, the software is less than most of its competitors."

"The price could be cheaper and it is best to negotiate the price."

"The price of Vertica is less expensive than some competitors, such as Teradata."

"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 solution is free and we pay for the storage."

"The pricing and licensing depend on the size of your environment and the zone where you want to implement."

"The pricing for this solution is very reasonable compared to other vendors."

More OpenText Analytics Database (Vertica) pricing and cost advice

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Top Industries

By visitors reading reviews

Computer Software Company

15%

Construction Company

13%

Comms Service Provider

Financial Services Firm

15%

Outsourcing Company

13%

Manufacturing Company

11%

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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

Questions from the Community

Ask a question

Earn 20 points

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.

See all answers

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...

See all answers

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...

See all answers

Comparisons

CockroachDB vs Citus Data

Compared 12% of the time

SQL Server vs Citus Data

Compared 10% of the time

Oracle Database vs Citus Data

Compared 10% of the time

YugabyteDB vs Citus Data

Compared 10% of the time

MariaDB vs Citus Data

Compared 2% of the time

More Citus Data Competitors

Teradata vs OpenText Analytics Database (Vertica)

Compared 7% of the time

Snowflake vs OpenText Analytics Database (Vertica)

Compared 6% of the time

Oracle Exadata vs OpenText Analytics Database (Vertica)

Compared 5% of the time

Microsoft Parallel Data Warehouse vs OpenText Analytics Database (Vertica)

Compared 5% of the time

SAP IQ vs OpenText Analytics Database (Vertica)

Compared 4% of the time

More OpenText Analytics Database (Vertica) Competitors

Product Reports

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October 2026

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Buyer's Guide

OpenText Analytics Database (Vertica)

October 2026

OpenText Analytics Database (Vertica) report

Download OpenText Analytics Database (Vertica) product report

Also Known As

No data available

Micro Focus Vertica, HPE Vertica, HPE Vertica on Demand

Overview

Citus Data transforms PostgreSQL into a distributed database, offering scalability for modern applications. It's designed for handling large data volumes by efficiently distributing workloads and providing fault-tolerant solutions that support business growth and operational efficiency.

As an extension for PostgreSQL, Citus Data combines the performance and power of PostgreSQL with the capability to scale across many nodes. This database offers full SQL functionality while distributing queries across multiple servers to manage large datasets. Known for its ability to handle both OLTP and analytical workloads, Citus Data enables businesses to achieve horizontal scalability with ease. The transparency in architectural configuration and integration with existing PostgreSQL tools make it a practical choice for data-driven organizations seeking performance and reliability.

What are the key features of Citus Data?

Distributed PostgreSQL: Transforms PostgreSQL into a distributed database, allowing horizontal scaling.
Real-Time Analytics: Supports real-time analytical queries across big data without significant latency.
Fault-Tolerance: Offers high availability with transparent sharding and replication strategies.
Elastic Scale-Out: Seamlessly adds nodes to your database to manage increasing loads without downtime.
Full SQL Support: Preserves full SQL functionality, making it easy to integrate with existing systems and tools.

What are the benefits and ROI of using Citus Data?

Scalability: Easily scales to meet expanding data requirements, reducing infrastructure limitations.
Cost-Efficiency: Helps lower costs by utilizing commodity hardware for scaling instead of expensive systems.
Performance Optimization: Improves data processing performance, which enhances end-user experiences.
Reduced Complexity: Simplifies operational management through automated distribution and easy node management.

In industries such as e-commerce, Citus Data is implemented to manage large-scale transactional data while providing real-time analytics for business insights. In finance, it supports high-frequency trading platforms, ensuring quick query responses under heavy loads. It also finds applications in healthcare, managing patient data securely and efficiently. For telecommunications, it powers data warehouses handling extensive user metadata. Each industry benefits from its scalable architecture and efficient data management capabilities.

Citus Data

OpenText Analytics Database Vertica enhances data processing with swift queries, scalability, and efficient compression, optimally managing enterprise-level data with minimal storage.

OpenText Analytics Database Vertica provides high availability clustering, columnar storage, and parallel processing to deliver fast data ingestion and real-time insights. Projections improve performance and simplify query tuning. The Management Console assists with administration, and integration with BI tools streamlines analytics. Adapted for handling large data volumes, Vertica supports data warehousing, ETL, geospatial analysis, and operational reporting across sectors such as media, finance, and telecom.

What are the most important features of OpenText Analytics Database Vertica?

Query Speed: Efficient processing for faster data queries.
Scalability: Supports large-scale data management seamlessly.
Data Compression: Reduces storage needs significantly.
High Availability: Ensures data remains accessible.
Columnar Storage: Enhances storage efficiency.
Parallel Processing: Boosts data handling capabilities.

What are the anticipated benefits and ROI when using OpenText Analytics Database Vertica?

Performance Efficiency: High-speed analytics and reduced maintenance demands.
Real-Time Insights: Swift data ingestion enables immediate decision-making.
Integration Ease: Works well with popular BI tools enhancing existing analytics.
Storage Savings: Column-oriented design leads to reduced storage costs.

Organizations in media, finance, and telecom rely on Vertica's capabilities to integrate with Power BI and Tableau, facilitating advanced data analytics and machine learning for business improvements. Its support for ETL processes, real-time processing, and geospatial analysis positions Vertica as critical for operational reporting and decision support systems.

OpenText

Sample Customers

Cloud Flare, Agari, Mix Rank, Heap

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

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October 2026

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