OpenText Analytics Database (Vertica) vs Oracle Autonomous Data Warehouse comparison

OpenText Analytics Database (Vertica) vs. Oracle Autonomous Data Warehouse

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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

OpenText Analytics Database...

Ranking in Cloud Data Warehouse

12th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Data Warehouse (7th)

Oracle Autonomous Data Ware...

Ranking in Cloud Data Warehouse

14th

Average Rating

8.4

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of September 2026, in the Cloud Data Warehouse category, the mindshare of OpenText Analytics Database (Vertica) is 5.0%, down from 6.0% compared to the previous year. The mindshare of Oracle Autonomous Data Warehouse is 4.2%, down from 5.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Mindshare Distribution
Product	Mindshare (%)
OpenText Analytics Database (Vertica)	5.0%
Oracle Autonomous Data Warehouse	4.2%
Other	90.8%

Cloud 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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reviewer1297710

IT Administrator at a manufacturing company with 1,001-5,000 employees

Analytics and data security needs are met but optimization requires improvement

We are using Oracle Autonomous Data Warehouse for analytics in my company The solution is used for analytics and it works for our data security needs. We continue to use it with satisfaction. Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not…

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Quotes from Members

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

Pros

"HP Vertica is an outstanding backend for Big Data-scale interactive dashboards/BI."

"Eighty percent of the ETL operations have improved since implementing this solution."

"Columnar storage makes 'hot data' available much faster than a traditional RDBMS solution."

"I would name HPE Vertica as the most mature columnar database with a best of class data storage and query engine."

"In other databases, information will return in hours or even days while in Vertica it will be finished in minutes or even seconds."

"Allows us to take volumes and process them at a very high speed."

"OpenText Analytics Database (Vertica) has impacted our organization positively because earlier we used to use Teradata, and it was very slow, creating issues with processing as well, and OpenText Analytics Database (Vertica) has helped us a lot in terms of processing capabilities and the speed of querying."

"Massive data ingestion performance."

More OpenText Analytics Database (Vertica) pros

"The solution is used for analytics and it works for our data security needs."

"I loved the simplicity of loading the data and simply relying on the self-tuning capabilities of ADW."

"It is a stable and scalable solution."

"The autonomous database provides several benefits and unmatched performance."

"With Oracle Autonomous Data Warehouse, things are much simpler. Creating a structure, initializing the servers, extending the servers, those are all things that are very, very easy. That's the main reason we use it."

"It provides Transparent Data Encryption (TDE) capabilities by default to address data security issues."

"The product has self-repair features."

"I really like the auto-tuning, auto-scaling, and the automatic load balancing and query tuning in the system."

More Oracle Autonomous Data Warehouse pros

Cons

"Support is an area where it could get better."

"Their support is really bad. Maybe Micro Focus has changed but they were not good before."

"Documentation has become much better, but can always use some improvement."

"vbr.py needs to be improve to support diff no of nodes source to target."

"If your product has lots of concurrent queries this solution is not suitable for you, or you need to implement a cache layer."

"But we're not sure yet, SQL Server is way more stable and predictable."

"The integration of this solution with ODI could be improved."

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

More OpenText Analytics Database (Vertica) cons

"One of the major problem is creating custom tablespace."

"I would like to see an on-premise solution in the future."

"The solution lacks visibility options."

"Ease of interconnectivity could be improved by which I mean setting up the VPN access and the like from on-premises to cloud."

"My main suggestion for Oracle is the configuration and key values that come for JSON files. When we create a table, especially if you see in our RedShift or some other stuff, if I create a table on top of a JSON file with multiple array columns or superset columns, those column values create some difficulty in Oracle."

"It doesn't work well when you have unstructured data or you need online analytics. It is not as nice as Hadoop in these aspects."

"Oracle Autonomous Data Warehouse is not available as an on-premises solution."

"The setup is complex."

More Oracle Autonomous Data Warehouse cons

Pricing and Cost Advice

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

"Vertica is an expensive tool."

"Read the fine print carefully."

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

"It is fast to purchase through the AWS Marketplace."

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

"Work with a vendor, if possible, and take advantage of more aggressive discounts at mid-fiscal year (April) and fiscal year-end (October)."

"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."

More OpenText Analytics Database (Vertica) pricing and cost advice

"The price depends on the configuration we choose."

"ROI is high."

"The solution's cost is reasonable."

"You pay as you go, and you don't pay for services that you don't use."

"Cloud solutions are cheaper, but in the long run, they may not be much cheaper. They certainly have a lower initial cost. The licensing is yearly, and it is based on the size of the hardware and the number of users."

"In terms of architecture and pricing structure, I feel it is a little bit costly compared to Azure. It's fine compared to RedShift, but compared to Azure, it's a bit pricey when you calculate for one TB storage plus around five hours of reporting with the frequency of 1TB data. The cost adds up, making Oracle a bit expensive."

"We pay approximately $70,000 per month. The cost includes maintenance and support."

"The solution is expensive."

More Oracle Autonomous Data Warehouse pricing and cost advice

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913,654 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

15%

Outsourcing Company

13%

Comms Service Provider

Computer Software Company

Financial Services Firm

11%

Media Company

10%

Manufacturing Company

Outsourcing 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

By reviewers
Company Size	Count
Small Business	7
Midsize Enterprise	1
Large Enterprise	11

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 is your experience regarding pricing and costs for Oracle Autonomous Data Warehouse?

We pay approximately $70,000 per month. The cost includes maintenance and support.

What needs improvement with Oracle Autonomous Data Warehouse?

Optimization should be better. The SQLs are sometimes very slow. I also noticed that Java is not supported, which is not ideal.

What is your primary use case for Oracle Autonomous Data Warehouse?

We are using Oracle Autonomous Data Warehouse for analytics in my company.

Snowflake vs OpenText Analytics Database (Vertica)

Comparisons

Compared 7% of the time

Teradata 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

IBM Netezza Performance Server vs OpenText Analytics Database (Vertica)

Compared 4% of the time

More OpenText Analytics Database (Vertica) Competitors

Snowflake vs Oracle Autonomous Data Warehouse

Compared 16% of the time

BigQuery vs Oracle Autonomous Data Warehouse

Compared 13% of the time

Microsoft Azure Synapse Analytics vs Oracle Autonomous Data Warehouse

Compared 10% of the time

Databricks vs Oracle Autonomous Data Warehouse

Compared 9% of the time

Oracle Exadata vs Oracle Autonomous Data Warehouse

Compared 3% of the time

More Oracle Autonomous Data Warehouse Competitors

Product Reports

OpenText Analytics Database (Vertica)

Download OpenText Analytics Database (Vertica) product report

OpenText Analytics Database (Vertica) report

Oracle Autonomous Data Warehouse

Download Oracle Autonomous Data Warehouse 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

Oracle Autonomous Data Warehouse is a cloud-based service offering advanced data management capabilities, including automated administration and high performance for analytics tasks. It is ideal for enterprises prioritizing security, easy maintenance, and dynamic scale.

Oracle Autonomous Data Warehouse stands out by offering self-managing capabilities that minimize administrative overhead, allowing organizations to focus on data-driven decision-making. With features such as transparent data encryption, seamless cloud integration, and automated query tuning, it ensures secure and efficient data operations. Its architecture separates compute and storage, enhancing scalability and performance. Despite its setup complexity and higher cost than some competitors, it offers deep integration with Oracle Database, ensuring reliable performance and fast data exchange.

What features define Oracle Autonomous Data Warehouse?

Self-Patching: Automatically updates to ensure security and performance.
Auto-Scaling: Dynamically adjusts resources to meet workload demands.
Query Tuning: Optimizes queries for better performance without user intervention.
Seamless Cloud Integration: Easily connects with Oracle and other cloud applications.
Transparent Data Encryption: Provides secure data handling to meet compliance needs.
Smart Scan: Efficiently processes queries to reduce data retrieval times.

What benefits can be expected from Oracle Autonomous Data Warehouse?

Cost-Effectiveness: Reduces operational costs through automation and serverless operations.
High Security: Ensures data protection with encryption and isolated resources.
Performance Enhancement: High-speed data processing and query response times.
Easy Maintenance: Minimal administrative tasks due to automation.
Scalability: Effortlessly scales resources to accommodate growth.

Oracle Autonomous Data Warehouse is widely used in finance, banking, transport, and manufacturing, supporting data analytics in financial systems, procurement, and student management. It facilitates large-scale transaction processing, offering centralized reporting and dynamic resource allocation, which is crucial for enhancing performance across industries.

Oracle

Sample Customers

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

Hertz, TaylorMade Golf, Outront Media, Kingold, FSmart, Drop-Tank

OpenText Analytics Database (Vertica) vs. Oracle Autonomous Data Warehouse