Oracle Big Data Appliance vs Teradata comparison

Oracle Big Data Appliance

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Executive SummaryUpdated on Oct 6, 2024

Teradata and Oracle Big Data Appliance compete in the big data industry. Oracle Big Data Appliance seems to have the upper hand due to its comprehensive features, which are preferred for robust applications.

Features: Teradata offers high scalability, handles complex queries efficiently, and demonstrates strength in data management. Oracle Big Data Appliance provides extensive data integration, enhanced analytics capabilities, and offers a comprehensive toolset for broader analytical insights.

Room for Improvement: Teradata could enhance data update speeds, improve compatibility with diverse data sources, and develop better real-time capabilities. Oracle Big Data Appliance can work on improving user accessibility, streamlining operational complexities, and providing more user-friendly configurations.

Ease of Deployment and Customer Service: Teradata deployment is smooth with effective customer support and minimal downtime. Oracle Big Data Appliance also has ease of deployment but requires specialized skills for optimal use. Teradata provides prompt solutions whereas Oracle offers a structured support system, albeit with complexity.

Pricing and ROI: Teradata's budget-friendly setup contributes to quicker ROI for smaller projects. Oracle Big Data Appliance is costlier but delivers substantial ROI through advanced capabilities, appealing to users focusing on comprehensive data solutions.

To learn more, read our detailed Oracle Big Data Appliance vs. Teradata Report (Updated: October 2024).

Oracle Big Data Appliance vs. Teradata

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Categories and Ranking

Oracle Big Data Appliance

Ranking in Data Warehouse

19th

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Teradata

Ranking in Data Warehouse

3rd

Average Rating

8.2

Number of Reviews

Ranking in other categories

Customer Experience Management (3rd), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of November 2024, in the Data Warehouse category, the mindshare of Oracle Big Data Appliance is 1.0%, down from 1.9% compared to the previous year. The mindshare of Teradata is 17.1%, up from 14.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Warehouse

Featured Reviews

Mohammed Hamad

AI & Data Engineering Lead at a tech services company with 10,001+ employees

May 20, 2022

Provides clean, centralized data

I use Big Data Appliance to have a single source of truth for my data and to keep all my data in one place Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the…

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SurjitChoudhury

Data engineer at Cocos pt

Feb 20, 2024

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

"Because Big Data Appliance allows me to have a single source of truth, it means I have clean data that can be monetized and leveraged to gain more insights with real-time reports from the dashboard."

"This is a comprehensive solution that is easy to deploy."

"The best thing about the product is that the end-user can build the reports by themselves without really knowing anything about databases."

"The two types of partitioning have been very significant for us - row and columnar partitioning."

"It is very stable. It's 100% uptime. Speed and resilience are one of the greatest features of this product. In almost twenty years we've never had downtime, except for outages for patches and upgrades. We've never had a system failure in twenty years."

"The most valuable feature of Teradata is the quick processing of large data."

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

"It effectively has allowed us to remove over 20 portion copies of the data sets on other DB platforms for real-time operational reporting purposes."

"It is a highly robust software solution."

"The most valuable features are the large volume of data and the structuring of the data to optimize it and get very optimal data warehouse solutions for customers."

"Teradata's capabilities enhance data management efficiency, support scalability, and contribute to faster query performance."

More Teradata pros

Cons

"It seems like the deployment of repositories has become more difficult in later versions of the product rather than easier."

"From a technical perspective, Big Data Appliance could be improved with more innovation in the AI and machine-learning parts instead of relying on Cloudera."

"The product should be simplified for the average user."

"It could be a bit more user-friendly."

"Teradata is an expensive tool. Like, if you're already using Microsoft products like Windows, they'll market all their products together. And with the rise of cloud technologies, companies will adopt solutions that offer them some privileges or facilities. Similar to how SAP does it in the market, so do Microsoft and other companies. Even Oracle and other such tools are quite commonly seen compared to Teradata's competitors in everyday solutions."

"If I want to implement an upgrade, I'd like to see how it will be different. Ideally, Data Lab should help me test production items and also do future things. Future releases should be downloadable and testable in Data Lab."

"The reporting side wasn't very good in the past, but with the latest versions, it's getting better. Still, the friendliness of the PDC reporting and functionality needs to be improved."

"There is some improvement required on OLTP level and some analytical function is missing."

"It could use some more advanced analytics relating to structured and semi-structured data."

"The solution is stable. However, there are times when we are using large amounts of data and we can see some latency issues."

"The cost of Teradata Cloud Data Warehouse has room for improvement."

More Teradata cons

Pricing and Cost Advice

"Oracle's prices are too high compared to others in the market."

"The solution requires a license."

"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

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

"The tool costs about 30,000 euros a month, while Azure Synapse SQL only costs 10,000."

"The price of Teradata is on the higher side, and I think that it where they lose out on some of their business."

"The initial cost may seem high, but the TCO is low."

"We had a lot of parties involved when purchasing from the AWS Marketplace. They are very flexible and aggressive in trying to close the deal. They are good at what they have to offer and listening to the customer. It's a two-way street."

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

Financial Services Firm

27%

University

12%

Government

12%

Computer Software Company

10%

Financial Services Firm

25%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

Ask a question

Earn 20 points

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...

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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...

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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,...

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Comparisons

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Compared 58% of the time

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Compared 42% of the time

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SQL Server vs Teradata

Compared 14% of the time

Oracle Exadata vs Teradata

Compared 14% of the time

Snowflake vs Teradata

Compared 9% of the time

MySQL vs Teradata

Compared 8% of the time

Vertica vs Teradata

Compared 5% of the time

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Product Reports

Data Warehouse

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Also Known As

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

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Oracle

Overview

Oracle Big Data Appliance is a flexible, high-performance, secure platform for running diverse workloads on Hadoop and NoSQL systems. With Oracle Big Data SQL, Oracle Big Data Appliance extends Oracle’s industry-leading implementation of SQL to Hadoop and NoSQL systems. By combining the newest technologies from the Hadoop ecosystem and powerful Oracle SQL capabilities together on a single pre-configured platform, Oracle Big Data Appliance is uniquely able to support rapid development of new Big Data applications and tight integration with existing relational data.

For more information on Oracle Big Data Appliance, visit Oracle.com

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

Caixa Bank

Netflix

Oracle Big Data Appliance vs. Teradata