Oracle Analytics Cloud vs Teradata comparison

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Oracle Analytics Cloud

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Executive SummaryUpdated on Jan 12, 2025

Teradata and Oracle Analytics Cloud are key players in data analytics and processing technologies. Teradata seems to stand out in terms of advanced parallel processing and scalability, while Oracle Analytics Cloud shows strength in user-friendly design and data visualization.

Features: Teradata is recognized for its advanced parallel processing capabilities, efficient query execution, and strong scalability, allowing it to handle large data volumes effectively. Its MPP architecture and security features help users in detailed performance tuning. Oracle Analytics Cloud offers robust data visualization and integration capabilities, with notable ease of deployment and varied analytics features. Its mobility and user-friendly design allow users to generate insights quickly across platforms.

Room for Improvement: Teradata needs to improve in areas of cloud adoption, pricing models, and integration with unstructured data. Enhancements in reporting and user interface design are also sought after. Oracle Analytics Cloud could benefit from enhanced visualization features, better user interaction, and more flexibility in pricing along with improved integration with advanced data science functionalities.

Ease of Deployment and Customer Service: Teradata offers flexible deployment options, including on-premises and hybrid cloud, with comprehensive support noted for its professionalism. However, occasional delays in technical support responses have been reported. Oracle Analytics Cloud is known for straightforward deployment across cloud environments, with high ratings in customer service, yet there is a call for improvements in the responsiveness of technical support.

Pricing and ROI: Teradata is seen as a high-end solution with robust capabilities, offering good ROI for large projects, although its high pricing encourages companies to consider more cost-effective alternatives. Oracle Analytics Cloud is viewed as less expensive than some competitors like Tableau, favored for its cost-effectiveness, customization benefits, and good ROI through customer satisfaction and scalable resources.

To learn more, read our detailed Oracle Analytics Cloud vs. Teradata Report (Updated: April 2025).

Oracle Analytics Cloud vs. Teradata

April 2025

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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

Oracle Analytics Cloud

Ranking in BI (Business Intelligence) Tools

8th

Average Rating

8.0

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Visualization (6th)

Teradata

Ranking in BI (Business Intelligence) Tools

10th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (6th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of April 2025, in the BI (Business Intelligence) Tools category, the mindshare of Oracle Analytics Cloud is 2.3%, down from 2.8% compared to the previous year. The mindshare of Teradata is 0.8%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

BI (Business Intelligence) Tools

Featured Reviews

Hafiz Abdul Mannan

Senior Consultant Oracle Technologies at Hewlett Packard Enterprise

Empowers your entire organization to ask any question of any data—across any environment, on any device

The migration of older dash tools from the classic interface of Oracle BI prior to OAS launch to the newer Data Visualization and Oracle Analytics Cloud interfaces, including dashboards and metadata, is currently a cumbersome process. Improvements in this area would be highly beneficial. Additionally, the administration of the cloud, particularly the startup of services and linking of the WebLogic server and integrated components, takes longer than desired. In today's enterprise landscape, waiting forty minutes for the server to be operational is quite lengthy; ideally, this process should take a maximum of four minutes. It would be excellent to incorporate metadata management as an integral part of the Oracle Analytics Cloud. When dealing with integrated data from various sources, tracking data lineage and the entire data life cycle, from sources to report development and the mapping of reports to specific dashboards, should be seamlessly managed within the Oracle Analytics Cloud. This would eliminate the need for additional tools. Drawing a comparison, tools like Tableau have a feature enabling metadata management, making it easier to trace the complete data lineage of reports. Managing over seven hundred and thirty-six business dashboards, the metadata management capability within Tableau simplified the process of understanding how reports were developed, including details like associated tables, users, linked views, materialized views, data segmentations, ETL jobs, and the data warehouse stages. Enhancing metadata tracking within the Oracle Analytics Cloud layout would facilitate easy and practical management of the complete data life cycle, encompassing user accessibility and report permissions.

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SurjitChoudhury

Data engineer at Cocos pt

Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities

We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

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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

"The best feature may be data flow, which is used to prepare and clean data."

"A valuable feature is the speed of the solution."

"It's really an enterprise solution. It has a dashboard, like standard dashboarding functionality. It also has reporting capabilities for producing pixel-perfect reports, bursting large volumes of a document if you need to. It has interactive data discovery functionality, which you would use to explore your data, bring your own data, and merge it with maybe the data from an enterprise data warehouse to get new insights from the pre-existing data. It has machine learning embedded in the solution. If you're new to machine learning, it's a really good way to get into it, because it's all within this platform, and it's really easy to use."

"The ability to quickly search for and access relevant data is crucial."

"The technical support services are good."

"The AI/ML enablement is useful, as many reporting tools do not offer machine learning models as of now, without writing customized code."

"The features that I find to be the most valuable are the BAS (Business Analytics), the Narrate feature, and the auto-visualization."

"I've discovered that the new layout of this product makes Docker sharing, machine learning support, and data backups more efficient. Unlike the older method of linking physical, pre-logical, and presentation layers separately, the new interface simplifies this process. Additionally, the integration of databases and machine learning is seamless, with the new visualization approach being particularly beautiful and highly beneficial."

More Oracle Analytics Cloud pros

"The solution scales well on the cloud."

"It's stable and reliable."

"The product's scalability is great. Scalability-wise, I rate the solution a ten out of ten."

"Things have started moving faster in my company, such as data retrieval happens more quickly."

"I like writing preformance queries for preprocessing on AWS Cloud."

"The key advantages are Performance when processing Terabytes of data and scalability."

"The most valuable feature is the ease of running queries."

"It's a pre-configured appliance that requires very little in terms of setting-up."

More Teradata pros

Cons

"When we have, for example, a table with low performance, we have several issues with drawing some graphics in the Oracle cloud."

"The learning curve should be improved, and I'm uncertain if tutorials are readily available or easily accessible. We may have resorted to looking on YouTube for such information. Having easily understandable documents or guides for new users would be beneficial. AI integration would be an interesting feature to add in the next release."

"It is expensive."

"One of the major issues is that Oracle Analytics Cloud is not user-friendly, requiring skilled people with proper certifications to work with it successfully."

"Its machine learning and visualization capabilities can be improved. There should be more visualization options."

"The product should be improved in terms of connectors; right now the top twenty connectors are available, but OneDrive and Teradata are missing."

"The solution could be more flexible."

"One area of improvement is associated with more connectors needing to be added such as Microsoft OneDrive, Teradata and a few others. I think the list is limited to the top ones now."

More Oracle Analytics Cloud cons

"Apart from Control-M, it would be nice if it could integrate with other tools."

"The solution needs improvement in its stability, support and pricing."

"There is a need to improve performance in high transaction processes, as well as the reporting system."

"The following could be better: licensing, architecture openness, integration with other tools."

"Teradata has a few AI models, but in data science, we need more flexibility."

"Teradata can improve the way it handles big data and unstructured data."

"The initial setup was complex as we had to rewrite a lot of the code."

"The solution could improve by having a cloud version or a cloud component. We have to use other solutions, such as Amazon AWS, Microsoft Azure, or Snowflake for the cloud."

More Teradata cons

Pricing and Cost Advice

"Oracle Analytics Cloud's pricing is generally higher than that of other vendors."

"I rate the product's pricing a nine on a scale of one to ten, where one is cheap, and ten is expensive."

"I would rate it a five out of five in terms of the value received for the price charge."

"The product’s pricing is expensive. However, feature-wise, it fits the requirements of enterprise customers."

"I don't know the exact cost, but its pricing was good. Its pricing was competitive. I would rate it a three out of five in terms of pricing."

"A highly cost-effective solution"

"We pay on a monthly basis and it is $10 per user each month."

"Bottom line, the cost is really, really cheap compared to other solutions. Oracle has made a huge effort on the pricing."

More Oracle Analytics Cloud pricing and cost advice

"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."

"It's a very expensive product."

"Teradata used to be expensive, but they have been lowering their prices."

"Teradata's licensing is on the expensive side."

"The solution requires a license."

"When looking into implementing this product, pricing is the main issue followed by technical expertise."

"Teradata is currently making improvements in this area."

"The cost is significantly high."

More Teradata pricing and cost advice

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Comparison Review

it_user232068

Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees

Aug 5, 2015

Netezza vs. Teradata

Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…

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Top Industries

By visitors reading reviews

Educational Organization

36%

Computer Software Company

Financial Services Firm

Government

Financial Services Firm

26%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Which Oracle product is better - OBIEE or Analytics Cloud?

Oracle OBIEE is designed to be relatively easy to set up and has a helpful customer support staff at the ready to assist customers. These are two attributes that make this system quite valuable. OB...

What do you like most about Oracle Analytics Cloud?

The ability to quickly search for and access relevant data is crucial.

What is your experience regarding pricing and costs for Oracle Analytics Cloud?

The pricing of Oracle Analytics Cloud is quite expensive, fitting for a premium tool. However, the cost raises expectations for partner support that are not met, especially for smaller companies wh...

Comparing Teradata and Oracle Database, which product do you think is better and why?

I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...

Which companies use Teradata and who is it most suitable for?

Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...

Is Teradata a difficult solution to work with?

Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...

Oracle OBIEE vs Oracle Analytics Cloud

Comparisons

Compared 25% of the time

Microsoft Power BI vs Oracle Analytics Cloud

Compared 14% of the time

Databricks vs Oracle Analytics Cloud

Compared 12% of the time

Oracle Business Intelligence Cloud Service vs Oracle Analytics Cloud

Compared 10% of the time

Tableau vs Oracle Analytics Cloud

Compared 9% of the time

More Oracle Analytics Cloud Competitors

Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 11% of the time

MySQL vs Teradata

Compared 7% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 7% of the time

More Teradata Competitors

Product Reports

Download Oracle Analytics Cloud product report

Oracle Analytics Cloud

March 2025

Download Teradata product report

March 2025

Also Known As

Oracle Analytics Cloud Service, OAC, Oracle Data Visualization, Oracle Data Visualization Cloud Service, ODV

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

Overview

Oracle Analytics is a complete platform with ready-to-use services for a wide variety of workloads and data.

Oracle Analytics allows businesses to add AI and machine learning capabilities to any application—and as part of our integrated suite of cloud services to comply with data security and connected without disrupting business operations.

Offering valuable, actionable insights from all types of data—in the cloud, on-premises, or in a hybrid deployment—Oracle Analytics empowers business users, data engineers, and data scientists to access and process relevant data, evaluate predictions, and make quick, accurate decisions.

Oracle Analytics Cloud Features

Oracle Analytics Cloud has many valuable key features. Some of the most useful ones include:

Intelligent search
Smart data discovery
Smart data preparation
Natural language
Auto suggest
Visualization
Dashboarding
Global transformation policies
Smart collaboration
Integrated data science
Enterprise architecture and security
Platform extensibility
Smart data connectors

Oracle Analytics Cloud Benefits

There are many benefits to implementing Oracle Analytics Cloud. Some of the biggest advantages the solution offers include:

Flexibility: Oracle Analytics Cloud gives you the flexibility to grow and change as your business does. At the same time, it puts you in complete control of your analytics environment by allowing you to analyze data and accommodate changing demand easily.

Scalable: Oracle Analytics Cloud is a single, centralized solution that provides everything you need in a scalable environment to support varied user requirements for your organization right now and in the future as well.

Comprehensive analytics: With Oracle Analytics Cloud, existing services are combined with new ones to deliver comprehensive analytics in the cloud. It provides everything you need for analytic agility, from fast, fluid self-service discovery to data loading and blending, inline data prep, data enrichment, automatic visualizations, data storytelling, and more.

Cost-effectiveness: The solution is cost-effective and reduces your total cost of ownership (TCO).
Innovation: Use the latest data analytics technologies, such as AI, machine learning, and natural language processing. Oracle Analytics has been recognized by industry experts for its innovations and robust architecture.

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the Oracle Analytics Cloud solution.

Fabricio Q., Data Analytics Manager, says, “The main functionality is great and everything is pretty standard and easy to use. It's great for consolidation and creating one source of truth. The initial setup is pretty straightforward.”

PeerSpot user, Eric B., Independent Consultant - Oracle BI Applications at Desjardins, mentions “It's really an enterprise solution. It has standard dashboarding functionality. It also has reporting capabilities for producing pixel-perfect reports, bursting large volumes of a document if you need to. It has interactive data discovery functionality, which you would use to explore your data, bring your own data, and merge it with maybe the data from an enterprise data warehouse to get new insights from the pre-existing data. It has machine learning embedded in the solution.”

Gaurav S., Vice President Credit Risk Management at a financial services firm, explains, “From a financial or bank perspective, this product is secure enough. The dashboards, analytics, visualizations, and different reports are valuable for business analytics. The AI/ML enablement is useful, as many reporting tools do not offer machine learning models as of now, without writing customized code.”

Another reviewer, Trinh P., Delivery Manager at Sift Ag, comments, "The specific capability I find important in Oracle Analytics Cloud is that it allows the basic user to easily drag and drop data. I also like that the solution allows the user to decide what to measure and what to see in the reports."

Oracle

Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.

As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.

What are the most important features of Teradata?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.

Sample Customers

Sejong Hospital

Netflix