

Teradata and BigQuery are leaders in the data warehousing category. Teradata is noted for its high-performance on-premises capabilities, while BigQuery shines with its cloud-native features, giving it an edge in scalability and integration with machine learning tools.
Features: Teradata is known for its ability to handle large data volumes through advanced parallel processing and robust query tuning capabilities. Its adaptability in deployment and comprehensive analytics toolset are highly valued. BigQuery is praised for its serverless architecture, scalability, and seamless integration with machine learning tools, which enhance flexibility and processing speed.
Room for Improvement: Teradata users desire better cloud compatibility, an easier user interface, improvements in handling unstructured data, and more advanced predictive analytics features. BigQuery users have pointed to high pricing, cache limitations on external tables, and UI improvements as areas needing enhancement.
Ease of Deployment and Customer Service: Teradata offers strong performance in on-premises and hybrid environments but faces challenges in scalability. Its customer service is generally well-regarded, though speedier response times are wanted. BigQuery excels in public cloud settings with easy setup, but support issues are associated with its lack of local presence.
Pricing and ROI: Teradata, while expensive, is suitable for large enterprises seeking premium analytics, offering substantial ROI through performance benefits. BigQuery presents a flexible pricing model, cost-effective for large-scale data tasks, although it can become expensive if not managed properly.
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%.
rating the customer support at ten points out of ten
I have been self-taught and I have been able to handle all my problems alone.
I would rate their customer service pretty good on a scale of one to 10, as they gave me access to the platform on a grant.
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.
It is a 10 out of 10 in terms of scalability.
The scalability is definitely good because we are migrating to the cloud since the computers on the premises or the big database we need are no longer enough.
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.
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.
Troubleshooting requires opening each pipeline individually, which is time-consuming.
In general, if I know SQL and start playing around, it will start making sense.
BigQuery is already integrating Gemini AI into the data extraction process directly in order to reduce costs.
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.
Being able to optimize the queries to data is critical. Otherwise, you could spend a fortune.
The price is perceived as expensive, rated at eight out of ten in terms of costliness.
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.
It is really fast because it can process millions of rows in just a matter of one or two seconds.
BigQuery processes a substantial amount of data, whether in gigabytes or terabytes, swiftly producing desired data within one or two minutes.
The features I find most valuable in this solution are the ability to run and handle large data sets in a very efficient way with multiple types of data, relational as SQL data.
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 | Market Share (%) |
|---|---|
| Teradata | 9.0% |
| BigQuery | 7.9% |
| Other | 83.1% |


| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 9 |
| Large Enterprise | 20 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 13 |
| Large Enterprise | 52 |
BigQuery is an enterprise data warehouse that solves this problem by enabling super-fast SQL queries using the processing power of Google's infrastructure. ... You can control access to both the project and your data based on your business needs, such as giving others the ability to view or query your data.
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.
We monitor all Cloud Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.