Oracle Database In-Memory vs Teradata comparison

Oracle Database In-Memory

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Executive SummaryUpdated on Oct 6, 2024

In the database management space, Teradata and Oracle Database In-Memory compete for user preference. Despite the higher cost, Oracle Database In-Memory gains the upper hand due to its performance and feature richness.

Features: Teradata stands out with its scalability, integration capabilities, and versatility. Oracle Database In-Memory is noted for its notable performance, analytical processing speed, and comprehensive feature set.

Room for Improvement: Teradata could improve real-time data processing, user interface simplicity, and reporting capabilities. Oracle Database In-Memory faces suggestions for better initialization, memory utilization efficiency, and reducing hardware dependency.

Ease of Deployment and Customer Service: Teradata offers a straightforward deployment process coupled with strong customer support. Oracle Database In-Memory has variability in setup complexity but maintains satisfactory customer service standards.

Pricing and ROI: Teradata is seen as cost-effective with a quick realization of ROI, attractive to those mindful of budget constraints. Oracle Database In-Memory, while more costly upfront, offers an ROI justified by its extensive features over time.

To learn more, read our detailed Oracle Database In-Memory vs. Teradata Report (Updated: October 2024).

Oracle Database In-Memory vs. Teradata

October 2024

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Categories and Ranking

Oracle Database In-Memory

Ranking in Relational Databases Tools

8th

Average Rating

8.8

Number of Reviews

Ranking in other categories

Embedded Database (3rd)

Teradata

Ranking in Relational Databases Tools

7th

Average Rating

8.2

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

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

Mindshare comparison

As of November 2024, in the Relational Databases Tools category, the mindshare of Oracle Database In-Memory is 1.4%, up from 1.1% compared to the previous year. The mindshare of Teradata is 5.2%, up from 4.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Relational Databases Tools

Featured Reviews

Duy AnhMai

Product Owner at Heineken

Sep 12, 2024

Improved data processing speeds with enhanced security and processing efficiency

We use Oracle Database In-Memory to deploy applications for commercial purposes, store data securely, and ensure efficient data processing Oracle Database In-Memory has improved data storage and processing efficiency, which is crucial for handling large amounts of data in our products and…

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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

"The application development is very user-friendly."

"The scalability of the solution is very good. It's able to support large amounts of data."

"It efficiently handles low-code data and supports read-and-write operations for clustering."

"The solution is very fast."

"The product offers high scalability."

"The most valuable aspects of this solution are the fast caching and improved performance to the database"

"Security is the most valuable feature."

"We find the dashboard and the speed of data processing very valuable in Oracle Database In-Memory."

More Oracle Database In-Memory pros

"It has a solid set of tools and consulting services."

"Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running."

"In Data Lab, you can schedule any testing you want to do in production. You can take a small subset of data from production, copy it there, and run all your tests. It reduces your testing costs because it's all in the lab."

"The feature that we find most valuable is its ability to perform Massive Parallel Processing."

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

"Improved performance of ETL procedures, reporting."

"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."

"Teradata can be deployed on-premise, on the cloud, or in a virtual machine, which means customers can move without having to create their architecture all over again."

More Teradata pros

Cons

"The pricing could be improved. It would ideal if it was more reasonable."

"Lacks sufficient integration with other tools."

"The solution is quite expensive."

"I would like Oracle Database In-Memory to include a data replication feature."

"The query optimization and backup features should be added."

"We often have to find solutions on our own through the support site, so there's room for improvement in this regard."

"We use some partitions in In-Memory. We have a very large table and a low dose. It is very expensive in data to load all of them into In-Memory. It takes up more memory slots in the server, as well as a lot of RAM. We use last partitions on the table. We always need to create a script and make a schedule that can load a last partition in In-Memory. Oracle doesn't have features to do this automatically. I would like them to allow us to load last partitions, as well as other table partitions, in In-Memory. I think a good feature would do that automatically, letting you see a table, load a large partition, and monitor loading memory. It's quite a good feature."

"They should lower the price. My customers think that it's too expensive."

More Oracle Database In-Memory cons

"The current operational approach needs improvement."

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

"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."

"An additional feature I would you like to see included in the next release, is that it needs to be more cloud-friendly."

"It is hard for some of our users to set up rules for cleansing and transforming data, so this is something that could be improved."

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

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

"Azure Synapse SQL has evolved from a solely dedicated support tool to a data lake. It can store data from multiple systems, not just traditional database management systems. On the other hand, Teradata has limitations in loading flat files or unstructured data directly into its warehouse. In Azure Synapse SQL, we can implement machine learning using Python scripts. Additionally, Azure Synapse SQL offers advanced analytical capabilities compared to Teradata. Teradata is also expensive."

More Teradata cons

Pricing and Cost Advice

"Database In-Memory is priced a bit higher than its competitors like Microsoft."

"There is a need to make a yearly payment towards the licensing costs, after which there is any to pay towards the support cost attached to the solution."

"Oracle Database In-Memory is expensive."

"I rate the pricing a zero out of ten because Database In-Memory is too costly."

"The pricing is pretty good so I rate it an eight out of ten."

"The solution's pricing is high."

"The platform's licensing cost needs improvement."

"It's quite costly and it comes with a fixed price."

More Oracle Database In-Memory pricing and cost advice

"The price of Teradata could be less expensive."

"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."

"The price of the solution could be reduced, it is expensive."

"I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services."

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

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

"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."

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

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

19%

Computer Software Company

12%

Manufacturing Company

11%

Government

Financial Services Firm

26%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Oracle Database In-Memory?

We can integrate it with any data sources as well.

What is your experience regarding pricing and costs for Oracle Database In-Memory?

Oracle Database In-Memory is very expensive. Additionally, there are extra costs for some features.

What needs improvement with Oracle Database In-Memory?

Oracle Database In-Memory is more expensive than Azure, and the support from the Oracle team is not very good, especially since they do not have a support team in our region.

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,...

SAP HANA vs Oracle Database In-Memory

Comparisons

Compared 24% of the time

SQL Server vs Oracle Database In-Memory

Compared 14% of the time

IBM Db2 Database vs Oracle Database In-Memory

Compared 13% of the time

Progress OpenEdge RDBMS vs Oracle Database In-Memory

Compared 10% of the time

MySQL vs Oracle Database In-Memory

Compared 8% of the time

More Oracle Database In-Memory Competitors

SQL Server vs Teradata

Compared 14% of the time

Oracle Exadata vs Teradata

Compared 13% 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

More Teradata Competitors

Product Reports

Oracle Database In-Memory

November 2024

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Download Teradata product report

October 2024

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 Database In-Memory transparently accelerates analytics by orders of magnitude while simultaneously speeding up mixed-workload OLTP. With Oracle Database In-Memory, users get immediate answers to business questions that previously took hours.

Oracle Database In-Memory delivers leading-edge in-memory performance without the need to restrict functionality, or accept compromises, complexity and risk. Deploying Oracle Database In-Memory with any existing Oracle Database compatible application is as easy as flipping a switch - no application changes are required. Oracle Database In-Memory is fully integrated with the Oracle Database’s renowned scale-up, scale-out, storage tiering, availability, and security technologies making it the most industrialstrength offering on the market.

The ability to easily perform real-time data analysis together with real-time transaction processing on all existing applications enables organizations to transform into Real-Time Enterprises that quickly make data-driven decisions, respond instantly to customer demands, and continuously optimize all key processes.

For more information on Oracle Database In-Memory, 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

Shanghai Customs

Netflix