SAP Analytics Cloud vs Teradata comparison

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SAP Analytics Cloud

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Executive SummaryUpdated on Jan 12, 2025

Teradata and SAP Analytics Cloud are well-regarded for business intelligence and analytics solutions. Teradata has the upper hand in handling large data volumes with its parallel processing capabilities, while SAP Analytics Cloud offers strong AI and machine learning integration.

Features: Teradata is adept at managing large data volumes with parallel processing and a robust Teradata Optimizer. It offers advanced analytics and extensive tool integration, suitable for various data environments. SAP Analytics Cloud features integrated AI and machine learning, enabling easy predictive analysis. Its strong integration with SAP ecosystems supports unified analytics, business intelligence, and planning.

Room for Improvement: Teradata could improve in cloud services, cost-efficiency, and integrating with newer platforms while addressing challenges with unstructured data. SAP Analytics Cloud needs better connectivity with non-SAP systems, enhancements in real-time data processing, and improved predictive analytics functionalities. Integration with legacy systems and pricing remain concerns.

Ease of Deployment and Customer Service: Teradata offers deployment options, including on-premises and hybrid clouds, but its on-premise focus may complicate cloud scaling. Customer service is rated well, though response times vary. Predominantly cloud-based, SAP Analytics Cloud offers ease of deployment with reliable customer support, yet response times in support and licensing access for less frequent users need improvement.

Pricing and ROI: Teradata is seen as costly, appealing to large enterprises for its scalability and performance, with newer pricing models offering flexibility. Users report good ROI, especially when its full analytical capabilities are utilized. SAP Analytics Cloud's premium pricing offers value with SAP tool integration. However, pricing can deter new users, although it provides excellent integration for SAP-centric firms.

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

SAP Analytics Cloud vs. Teradata

January 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

SAP Analytics Cloud

Ranking in BI (Business Intelligence) Tools

4th

Average Rating

8.0

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

Predictive Analytics (2nd)

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 (4th), Backup and Recovery (20th), Data Integration (17th), Relational Databases Tools (7th), Data Warehouse (3rd), Marketing Management (6th), Cloud Data Warehouse (6th)

Featured Reviews

RamasamyTelungupalayam

Product Manager - ERP Analytics and BI at Haleon

Seamless integration, collaborative features, and enhances data exploration

There are several areas for improvement in SAP Analytics Cloud. Firstly, features available in SAP Lumira are missing in SAP Analytics Cloud. Secondly, the predictive analytics functions, although promising, are currently only suitable for Proof of Concepts (POCs) and not for industrial-scale use. Lastly, the pricing model for the planning functionality is quite high and presents an entry barrier.

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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

"Offers both business intelligence as well as inbuilt AI and machine learning capabilities."

"SAP Analytics Cloud is very easy to use, and you don't require much technology. It has a very good library and analytics. It is easy to configure and offers good visualization."

"The most useful feature of SAP Analytics Cloud is planning because it helps users with making predictions and forecasts. Clients can forecast, make data allocations, and other actions. The solution is useful for planning."

"Provides rich features for developing automated reports and dashboards."

"It is easy to integrate with SAP ERP and BW systems, allowing smooth data transfer and live connections without much development."

"The most valuable feature of the tool is machine learning."

"It's so user-friendly."

"It's easy to connect Analytics Cloud with other SAP solutions, and it's also effortless to deploy. You don't need much technical skill to set it up. It's as easy as setting up a tablet. I said tablet before. It's very easy to actually set up."

More SAP Analytics Cloud pros

"Designing the database is easy."

"Building a data warehouse with Teradata has definitely helped a lot of our downstream applications to more easily access information."

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

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

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

"The ability to handle machine data parallel processing is the most valuable feature of Teradata."

"Cuts time to process huge amounts of data with efficient analytical queries."

"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."

More Teradata pros

Cons

"When it comes to planning there is a concern about the ability to match the exact requirements of the customer with what the product offers."

"Statistical analysis should be a bit more profound than it is."

"Sometimes we have difficulty connecting to a SharePoint list."

"It is very expensive."

"SAP has always had one problem with its products, they make them very closed systems that are difficult to integrate."

"I think it would be easier if there was another module created to retrieve only data."

"The technology used by the tool is old, making it an area where improvements are required."

"They need a better scalability rate."

More SAP Analytics Cloud cons

"Since I was working on the very basic, legacy systems, the memory thing was always a challenge. If Teradata is moving to the cloud, the space constraint or the memory issue that my company generally faces will eventually resolve, in time. What I'd like to see in the next release of Teradata is that it becomes full-fledged on the cloud, apart from better connectivity to various systems. For example, if I have to read or include a Python script, if I write some basic codes, I should be able to read even unstructured data. I know that it's not supported even in Snowflake, but at least semi-structured data support, if that can be a little more enhanced, that would be good."

"Teradata's pricing is quite high compared to Redshift, Synapse, or GCP alternatives."

"Teradata should focus on functionality for building predictive models because, in that regard, it can definitely improve."

"I would like more security and speed."

"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."

"Teradata is an old data warehouse, and they're not improving in terms of new, innovative features."

"Their level of technical support is adequate. It could be better."

"The tool's flexibility and capacity for expansion are areas of concern where improvements are required."

More Teradata cons

Pricing and Cost Advice

"The pricing of this product is reasonable."

"The premium option is very expensive at five thousand dollars. I use the nine hundred and ninety-nine dollar option."

"It's quite expensive and costs a lot to maintain, especially with licensing."

"This solution offers value for money and you get what you pay for."

"Its price is slightly on the higher side."

"The price is competitive. There is a power user license and normal user license, but the normal user license is reasonable."

"I don't have the exact price for SAP Analytics Cloud, but it could be improved and made cheaper, especially when compared to Power BI."

"SAP Analytics Cloud is expensive. The price is a big issue if you compare it with other solutions from different vendors."

More SAP Analytics Cloud pricing and cost advice

"The cost of running Teradata is quite high, but you get a good return on investment."

"The product cost is high for what the client gets. There may be more cost-effective solutions for small and medium-sized organizations."

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

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

"It comes at a notably high cost for what it offers."

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

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

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

26%

Manufacturing Company

14%

Computer Software Company

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

Which would you choose - Tableau or SAP Analytics Cloud?

Tableau is easy to set up and maintain. In about a day it is possible for the entire platform to be deployed for use. This relatively short amount of time can make all the difference for companies ...

What do you like most about SAP Analytics Cloud?

In the data warehouse, you're free to make changes. You can make everything text, meaning it's always a string. Even numbers appear as text, giving you the flexibility to work with all columns.

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

The pricing model for SAP Analytics Cloud is quite competitive, but the cost for the planning functionality is high and can be a barrier to entry. The overall cost can be managed with better billin...

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 BusinessObjects Business Intelligence Platform vs SAP Analytics Cloud

Comparisons

Compared 18% of the time

Tableau vs SAP Analytics Cloud

Compared 17% of the time

IBM Planning Analytics vs SAP Analytics Cloud

Compared 12% of the time

Microsoft Power BI vs SAP Analytics Cloud

Compared 10% of the time

Anaplan vs SAP Analytics Cloud

Compared 8% of the time

More SAP Analytics Cloud Competitors

Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 12% of the time

MySQL vs Teradata

Compared 8% of the time

Snowflake vs Teradata

Compared 8% of the time

Amazon Redshift vs Teradata

Compared 6% of the time

More Teradata Competitors

Product Reports

Download SAP Analytics Cloud product report

SAP Analytics Cloud

December 2024

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December 2024

Also Known As

SAP BusinessObjects Cloud

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

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SAP

Overview

SAP Analytics Cloud is an all-in-one Software-as-a-Service business intelligence tool that provides the key functionalities of an analytics tool to SAP business users. This tool is built on HANA Business Intelligence (BI) platform, providing analytics from data collected from multiple sources, such as ERP, Microsoft SQL, and Salesforce, among other solutions.

You can use SAP Analytics Cloud to compile data and perform ad-hoc reporting and analysis for predictive planning. SAP Analytics Cloud collects and analyzes the raw data from transactional systems into intelligent insights that allow you to make better decisions.

SAP Analytics Cloud uses machine learning to clean up data, identify errors, and issues, and suggest optimization or filtering options. You can use the modeling feature in Analytics Cloud to create hierarchies and get deeper data insights.

The three core functions of SAP Analytics Cloud consist of Planning, Predictive Analysis, and Business Intelligence as a holistic SaaS solution that offers real-time analysis to business leaders.

SAP Analytics Cloud Capabilities

Data discovery
Machine learning
Integrated financial and business planning
Predictive analysis
Automated data cleansing
Custom widgets
Mobile extension
Role-based customization
Data exploration and visualization

SAP Analytics Cloud Key Features

Augmented analytics: SAP Analytics Cloud allows organizations to make the most of AI (Artificial Intelligence)-powered analytics through augmented analytics. It includes a Search to Insight feature that enables users not skilled or experienced in data science to access and use the platform.

These smart insight tools allow organizations to visualize business data without manual intervention. By combining multiple machine learning algorithms, SAP Analytics Cloud automates predictive analysis so that organizations can have significant insight into secured data.

Enterprise planning: As SAP Analytics Cloud is an all-in-one financial planning and analysis solution, organizations can use it to align strategies across all departments. It allows end-to-end, data-driven planning decisions via financial modeling, allocations, smart insights, and automated reporting.

The Zero-based budgeting feature allows for an effective resources allocation with built-in collaboration tools. The finance team can collaborate easily, create budget templates and make accurate decisions.

SAP Analytics Cloud Benefits

Real-time cloud insights: SAP Analytics Cloud makes it easy for users at every level to generate instant insights and improve data-driven decision-making. With SAP Analytics Cloud, you can have immediate and central access to all figures, diagrams, insights, and evaluations for every employee on every device and updated in real time.
Customizable dashboard: You can customize your dashboard according to your requirements. This customization means you can easily access all the relevant data on a single pane of vision tailored to your business.
Collaborative planning: As an all-in-one platform, SAP Analytics Cloud integrates the multiple aspects of a business into a single solution, including finance, HR, sales, and supply chain management.
Data on any device: You can integrate SAP Analytics Cloud with SAP S/4 HANA and deploy insights to Android and iOS devices. The SAP S/4 HANA integration also enables the rolling out of changes to multiple files and devices from a central location, so you can carry your business operations on the go over a secured cloud network.
In-memory technology: Since it is based on SAP HANA in-memory technology, SAP Analytics Cloud can process massive amounts of data in a short time.

Reviews from Real Users

Segun O., SAP HANA Developer at SOA PEOPLE, says that "The most valuable features are on the application side, where you can design applications into your analytics on the platform."

The Head of Finance Enterprise Application at a computer software company adds that "The visualization feature is the most valuable. SAP Analytics Cloud is also very easy to use."

"Its many features make it the best in the market," sums up a Consultor SAP Business Object, Sap Analytics Cloud at a tech services company.

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

Live Oak Bank

Netflix