SAP HANA vs SAS Viya

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Our analysts compared SAP HANA vs SAS Viya based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

SAP HANA Software Tool

Product Basics

SAP HANA is the in-memory database for SAP’s Business Technology platform with strong data processing and analytics capabilities that reduce data redundancy and data footprint, while optimizing hardware and IT operational needs to support business in real time. Available on-premise, in the cloud and as a hybrid solution, it performs advanced analytics on live transactional data to display actionable information.

With an in-memory architecture and lean data model that helps businesses access data at the speed of thought, it serves as a single source of all relevant data. It integrates with a multitude of systems and databases, including geo-spatial mapping tools, to give businesses the insights to make KPI-focused decisions.
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SAS Viya is a cloud-based in-memory analytics engine that provides data visualization, reporting and analytics to businesses for actionable data insights. Powered by AI, it brings together visual analytics, visual statistics and data science for enterprises to achieve end-to-end self-service analytics. It uses a standardized code base with support for programming in R, Python, SAS, Java and Lua.

Deployable in the cloud, on-premises and hybrid environments, it integrates with a wide range of business applications through an agile, scalable architecture. The vendor offers an introductory 30-day free trial.

Pros
  • Comprehensive features
  • Powerful analytics capabilities
  • User-friendly interface
  • Scalable architecture
  • Strong support from SAS
Cons
  • Steep learning curve
  • Limited customization options
  • High cost of ownership
  • Potential vendor lock-in
  • Resource-intensive
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$972/Capacity Unit, Usage-Based
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Tailored to your specific needs
$10,000 Annual
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Tailored to your specific needs
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Product Assistance

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Knowledge Base
24/7 Live Support
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24/7 Live Support

Product Insights

  • Database Management: Reduces operational complexity through the use of a single database that allows data to be stored without a predefined structure. Provides data structure flexibility to application developers. Joins this data with many other data types with full interoperability. 
  • Build Business Solutions: The Business Function Library delivers pre-built functions that developers link at the database kernel level to build powerful business solutions. 
  • Geo-spatial Analysis: Stores spatial data and enables geographical data processing to drive location-specific business application development. 
  • Deploy Anywhere: Deploy on-premise, multi-cloud or go hybrid. Set up on traditional servers, pre-configured appliances, the HANA Enterprise Cloud or partner clouds including AWS and Microsoft Azure. Extend on-premise solutions to the cloud smoothly during any phase of the project. 
  • Predictive Analytics and Machine Learning: Supports transactional processing through machine learning and data analysis in real time. Take action before or as events happen to improve results and boost productivity. 
  • Smart Data Access: Connect virtually to remote, externally supported databases. Stores only the metadata of the database objects as a virtual table in the local database schema. Access data from the remote database in real time, irrespective of its location. 
  • Reduced Cost of Ownership: Mitigates hardware costs through a reduced data footprint made possible by a compression algorithm and lean data structure. 
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  • Improve Decision-Making: Make informed business decisions by using historical and current proprietary information to derive analytical insights. Compute vast amounts of data faster and resolve complexities through parallel processing. Boost workflow efficiencies by deploying operational decisions that define real-time best actions at scale. 
  • Self-Service Analytics: Easily perform automated forecasting, goal-seeking and scenario analysis — no technical skills needed. Identify user sentiment through text analytics and incorporate geographical data for a complete picture of business metrics. 
  • Maximize ROI: Save time through built-in automation for data prep, feature engineering, algorithm selection and AI-powered data discovery. Innovate, rather than spending time on tedious data management and analytics tasks. 
  • Data Security: Ensure data encryption at rest and while moving across systems, in addition to auditing protocols. Connect to external data management systems like Oracle, Teradata, Facebook, Amazon and Esri seamlessly through Kerberos, SAML, OAuth and OpenID. 
  • Data Management: Import data by using an IDE or through REST APIs, and visualize and analyze it through self-service data prep. Join tables, apply functions and perform calculations, or drag-and-drop, pivot, and slice and dice to view desired metrics. 
  • Augmented Analytics: Identify relationships in data through automatically generated suggestions and guided analysis, and track anomalies and outliers. Tell data stories by generating easy-to-understand visuals and dashboard summaries in natural language. Derive meaningful insights for the future by creating what-if scenarios for forecasting and predictive analytics. 
  • Mobility: Access business reports on the go through a native mobile app that supports a variety of charts, graphs and tables. Configure app functionality per device for specific users to add and view reports, share links, add and view comments and view alerts. 
  • Scalable Architecture: Leverage its modular microservices architecture to scale as per business needs. Monitor and manage the health and configuration of individual microservices instances through the SAS Environment Manager. Deploys seamlessly to any type of environment, including the cloud, and runs on Cloud Foundry as a platform-as-a-service (PaaS). 
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  • Data Integration: Captures any type of data — structured or unstructured — from database transactions, applications and streaming data sources. Ingests part of a data set or the complete data set into its native architecture for ready access. 
  • Capture and Replay: Record complex database transactions and then replay them on another device. Test on a non-production system while using production transactions, on a hosted instance, or in the cloud. 
  • Graph Data Processing: Combines its built-in graph engine with the in-memory relational database. Makes graph processing of relational tables easy to learn and use. 
  • SAP HANA Cockpit: Configure and manage HANA instances and applications through a single console interface. Easily schedule all backup jobs and monitor the system for immediate visibility of potential blockers. Integrate with other applications for workload management and security. 
  • Flexible Querying: Choose from a variety of semantics structures to query data in the database memory through a flexible algorithm. 
  • In-memory Architecture: Analyze insights in real time to monitor business KPIs and generate forecast trends. Access data quicker than with conventional databases via its in-memory database. 
  • Data Compression: Compresses data by up to 11 times and stores it in columnar structures for high-performance read and write operations. Saves storage space and provides faster data access for search and complex calculations. 
  • Parallel Processing: Performs basic calculations, such as joins, scans and aggregations in parallel, leveraging column-based data structures. Processes data quicker for distributed systems. 
  • Real-time Analysis: Queries transactional data directly as it is added in real-time. Leverages its inbuilt data processing algorithm to read and write data to a column storage table at high speeds. Acquire total visibility over information while it is being analyzed and make on-the-spot, incisive decisions. 
  • Role-based Permissions: Maintain data integrity across the organization — assign data access based on each team member’s role. 
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  • Visualization and Reporting: Dig into data for in-depth analysis and view key business metrics through autonomous data exploration and manipulation. Create and customize interactive reports and charts to share with others across the organization for collaborative insight. Get suggestions on graphics best suited to display pertinent data through auto charting. 
  • Data Modeling: Analyze data with predictive models through regression, clustering and neural networks. Ensure version control by tracking data models from creation through usage by registering, validating and monitoring each version. Creates snapshots of model properties and files and retains them for the future. 
  • Visual Statistics: Build diverse scenarios simultaneously and refine them with what-if analyses to uncover insights through experimentation. Unifies all business tools, irrespective of the language they support, into a common visual analytics solution. 
  • Cloud Integrations: Develop low-code technologies by porting SAS open-source models into mobile and business applications through its cloud-native capability. Optimize analytics workloads on clouds like Microsoft Azure and ensure cost-efficient migration of analytics to the cloud through a workload management tool. 
  • ML-Based Insights: Get valuable insights from new data types by combining structured and unstructured data in integrated machine learning programs. Choose the desired ML algorithm from a range of options and easily find the optimal parameter settings. Use Python within Jupyter notebooks for deep learning functions like computer vision, natural language processing, forecasting and speech processing. 
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Product Ranking

#13

among all
Big Data Analytics Tools

#41

among all
Big Data Analytics Tools

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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Augmented Analytics Computer Vision And Internet Of Things (IoT) Dashboarding And Data Visualization Data Management Data Preparation Geospatial Visualizations And Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 96 100 98 96 86 93 70 96 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Great User Sentiment 1173 reviews
Great User Sentiment 203 reviews
86%
of users recommend this product

SAP HANA has a 'great' User Satisfaction Rating of 86% when considering 1173 user reviews from 4 recognized software review sites.

85%
of users recommend this product

SAS Viya has a 'great' User Satisfaction Rating of 85% when considering 203 user reviews from 3 recognized software review sites.

4.2 (345)
4.2 (157)
4.6 (19)
4.3 (33)
4.3 (328)
4.7 (13)
4.3 (481)
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Awards

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SelectHub research analysts have evaluated SAS Viya and concluded it deserves the award for the Best Overall Big Data Analytics Tools available today and earns best-in-class honors for Augmented Analytics and Computer Vision and Internet of Things (IoT).

Analysts' Pick Award
Augmented Analytics Award
Computer Vision and Internet of Things (IoT) Award

Synopsis of User Ratings and Reviews

Data Analysis: Around 92% of users who reviewed data analysis said that the tool analyzes and displays insights and trend forecasts of transactional data in real time to enable timely decision-making.
Data Processing: Approximately 91% of the users who discussed data processing said that the tool can query large amounts of data due to its in-memory architecture and data compression algorithm.
Data Integration: Around 87% of the users said that the solution migrates data efficiently from a wide range of SAP and non-SAP systems.
Support: Approximately 87% of the users who discussed support said that they are responsive, and online user communities and knowledge bases assist in faster resolution of issues.
Speed and Performance: Citing the tool’s fast runtime, around 76% of the users said that they can perform on-the-fly calculations at very high speeds.
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Ease of Use: All users who mention its interface say that it makes autonomous analysis and data modeling accessible to users of all skill levels.
Support: All users who review support say that representatives are responsive and helpful in resolving issues and queries.
Functionality: Around 71% of the users who comment on its feature set say that the software helps discover data insights through powerful visualizations and on-the-fly calculations.
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Pricing: Approximately 80% of the users who mentioned pricing said that the solution’s in-memory architecture demands large amounts of RAM, which adds to the cost.
Functionality: According to around 53% of the users who reviewed functionality, the solution needs to be more flexible and agile to perform complex calculations on large datasets.
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Cost: All users who discuss its pricing say that the cost of acquisition is high.
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SAP HANA is a multi-model database and analytics platform that combines real-time transactional data with predictive analytics and machine learning capabilities to drive business decisions quicker. Most of the users who mentioned analytics said that, with its Online Analytical Processing(OLAP) and Online Transactional Processing(OLTP) capabilities, the tool analyzes data faster with predictive modeling and machine learning. Many users who reviewed data processing said that the tool has a lean data model due to its in-memory architecture and columnar storage capabilities, and, paired with its compression algorithm, can perform calculations on-the-fly on huge volumes of data. In reference to data integration, many users said that the platform connects seamlessly with both SAP and non-SAP systems, such as mapping tools like ArcGIS, to migrate data to a consolidated repository, though quite a few users said that integration with media files and Google APIs is tedious. Most of the users who reviewed support said that they are responsive, and online user communities and documentation help in resolving issues, whereas some users said that the support reps had limited knowledge. A majority of the users who reviewed its speed said that the platform has a fast runtime, though some users said that it requires high-performing hardware infrastructure to do so and that memory management might be tricky with large datasets. The software does have its limitations though. Being in-memory, the tool is RAM-intensive, which can add to the cost of ownership, though some users said that data compression reduces the database size and saves on hardware cost. A majority of the users who reviewed its functionality said that it needs to be more mature in terms of flexibility and agility, though some users said that with easy updates and maintenance, it is a robust solution and increases efficiency and productivity. In summary, SAP HANA serves as a single source of truth for analysis of large volumes of data and uncovering consumer insights through planning, forecasting and drill-down reporting. However, it seems more suited for large organizations with complex data types and analytics workflows because of its costly pricing plans.

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SAS Viya is an AI-powered data management and visual analytics platform with a robust, scalable architecture. All users who reviewed data source connectivity said that it connects to multiple sources and integrates easily with business applications, giving a seamless user experience. With fast in-memory processing of big data sets, it leverages the power of R to enable visual statistics. All users who mentioned predictive analysis said that it enables automated forecasting through what-if scenarios, goal-seeking, text mining and decision trees. Citing ease of use, all users say that the platform is intuitive and enables easy data modeling and self-service visual analytics. All users who mentioned support said that they are responsive and knowledgeable. Around 71% of the users who comment on its functionality say that it is a robust, scalable and flexible platform that enables visualization and analysis of business data, though some users say visual statistics need improvement. On the flip side, all users who review its cost say that the tool is expensive. In summary, SAS Viya is an analytics tool that provides data management, visualization and AI-powered analytics to enterprises for improved decision making, though small organizations and startups might find it cost-prohibitive.

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