Find out what your peers are saying about Oracle, PostgreSQL, ClickHouse and others in Open Source Databases.
I have seen a return on investment with MySQL, as it allows us to manage with fewer employees, focusing on business logic rather than database management.
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.
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.
At least fifteen to twenty percent of our time has been saved using Teradata, which has positively affected team productivity and business outcomes.
Independent research showed that Teradata VantageCloud users achieved an average ROI of 427% across three years with payback under a year, demonstrating the platform's ability to deliver a strong financial return.
We have realized a return on investment, with a reduction of staff from 27 to eight, and our current return on investment is approximately 14%.
I would rate the documentation and online support a 10 out of 10.
We have no issues and usually receive timely responses.
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.
Overall, our experience with OpenText Analytics Database (Vertica) customer support has been good and reliable.
The customer support for Teradata has been great.
They are responsive and knowledgeable, and the documentation is very helpful.
Customer support is very good, rated eight out of ten under our essential agreement.
Meeting scalability requirements through cloud computing is an expensive affair.
MySQL's scalability is currently adequate, as we have increased operations from ten thousand to twelve thousand devices, and it is working fine for us.
We have experienced easy horizontal scaling, consistent query performance as data grew, and the ability to handle large analytic workloads.
OpenText Analytics Database (Vertica) has very good scalability.
OpenText Analytics Database (Vertica) can scale to a great extent.
Whenever we need more resources, we can add that in Teradata, and when not needed, we can scale it down as well.
This flexibility allows organizations to scale according to their needs, balancing performance, cost, and compliance requirements.
This expansion can occur without incurring downtime or taking systems offline.
We face certain integration issues, especially when we integrate the database with security solutions like IBM QRadar.
From my experience, MySQL was pretty stable.
OpenText Analytics Database (Vertica) is very stable.
Its massively parallel process architecture allows the platform to distribute workload efficiently, enabling organizations to run heavy analytic queries without compromising speed or stability.
I find the stability to be almost a ten out of ten.
The workload management and software maturity provide a reliable system.
It could be more beneficial if MySQL can enhance its data masking functionality in the same way it has improved data encryption.
Oracle could improve on scalability.
The load balancer, MySQL LB, which is used to connect to the application, lacks clear documentation.
Smarter automatic projection management is needed with more intelligence, auto projection creation, automatic optimization, and reduced manual testing with better workload management.
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.
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.
I want to highlight two features for improvement: first, storing data in various formats without requiring a tabular structure, accommodating unstructured data; and second, adding AI ML features to better integrate Gen AI, LLM concepts, and user-friendly experiences such as text-to-SQL capabilities.
Unlike SQL and Oracle, which have in-built replication capabilities, we don't have similar functionality with Teradata.
The most challenging aspect is finding Teradata resources, so we are focusing on internal training and looking for more Teradata experts.
Oracle has different components, so if you need security, you have to procure a different license, but here everything is inbuilt and it's not costly.
The pricing for OpenText Analytics Database (Vertica) is somewhat on the higher side for the license.
Teradata is much more expensive than SQL, which is well-performed and cheaper.
Initially, it may seem expensive compared to similar cloud databases, however, it offers significant value in performance, stability, and overall output once in use.
Role-based access control (RBAC), strong audit and compliance features, high availability, fault tolerance, and encrypted data at rest and in-transit are key features.
With Oracle, we have to buy another solution for encryption and masking, but MySQL supports native encryption, which enhances our return on investment.
The main feature we utilize in MySQL is the view, and I can say that it is the most valuable feature for our needs.
It allows programming, writing stored procedures, creating views, constraints, and triggers easily.
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.
Projection and columnar storage are the most valuable features because they dramatically improve query performance and reduce the need for index management.
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.
Teradata's security helps our organization meet compliance requirements such as GDPR and IFRS, and it is particularly essential for revenue contracting or revenue recognition.
Its architecture allows information to be processed efficiently while maintaining stable performance, even in highly demanding environments.
It facilitates data integration, where we integrate and analyze data from various sources, making it a powerful and high-quality reliable solution for the company.
| Product | Mindshare (%) |
|---|---|
| MySQL | 10.3% |
| PostgreSQL | 14.4% |
| Firebird SQL | 11.9% |
| Other | 63.4% |
| Product | Mindshare (%) |
|---|---|
| OpenText Analytics Database (Vertica) | 5.0% |
| Snowflake | 10.2% |
| Teradata | 9.0% |
| Other | 75.8% |
| Product | Mindshare (%) |
|---|---|
| Teradata | 9.0% |
| Snowflake | 10.2% |
| Oracle Exadata | 8.1% |
| Other | 72.7% |


| Company Size | Count |
|---|---|
| Small Business | 75 |
| Midsize Enterprise | 33 |
| Large Enterprise | 61 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 23 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
MySQL is an open-source database known for its ease of use and high performance. It offers features like replication and clustering, making it ideal for diverse applications. Its cost-effectiveness and LAMP integration are key advantages for businesses.
MySQL supports a variety of languages and platforms, providing reliable, scalable data management. Its graphical interface and LAMP architecture integration enhance its usability, while community support further strengthens its appeal. Challenges include scalability issues with large databases, lack of advanced clustering, and limited high-availability features. Complex queries may affect performance, and integration can pose difficulties. The outdated interface and insufficient documentation are also concerns, along with replication and backup reliability issues.
What are MySQL's key features?MySQL is widely implemented in industries such as web development, e-commerce, and finance. It's used for managing dynamic websites, powering e-commerce platforms, and supporting financial applications. Its compatibility with PHP and cost-effectiveness make it suitable for CMS platforms like WordPress. With cloud services integration, MySQL is a backend choice for scalable applications in various sectors.
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?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.
Teradata is a powerful tool for handling substantial data volumes with its parallel processing architecture, supporting both cloud and on-premise environments efficiently. It offers impressive capabilities for fast query processing, data integration, and real-time reporting, making it suitable for diverse industrial applications.
Known for its robust parallel processing capabilities, Teradata effectively manages large datasets and provides adaptable deployment across cloud and on-premise setups. It enhances performance and scalability with features like advanced query tuning, workload management, and strong security. Users appreciate its ease of use and automation features which support real-time data reporting. The optimizer and intelligent partitioning help improve query speed and efficiency, while multi-temperature data management optimizes data handling.
What are the key features of Teradata?
What benefits and ROI do users look for?
In the finance, retail, and government sectors, Teradata is employed for data warehousing, business intelligence, and analytical processing. It handles vast datasets for activities like customer behavior modeling and enterprise data integration. Supporting efficient reporting and analytics, Teradata enhances data storage and processing, whether deployed on-premise or on cloud platforms.