Looker Studio vs SAP HANA

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Our analysts compared Looker Studio vs SAP HANA 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

Google Looker Studio is a robust data analytics and business intelligence platform designed to help organizations extract valuable insights from their data. It offers a user-friendly interface for data exploration, powerful visualization tools, and real-time data monitoring. Key features include customizable dashboards, SQL-based queries, and seamless data integration from various sources. Users can collaborate within the platform, fostering a data-driven culture. Looker Studio empowers users to make data-informed decisions, with the ability to create tailored reports and leverage machine learning for predictive analytics. It suits businesses of all sizes and industries, facilitating scalable analytics and promoting data-driven decision-making.
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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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$3,000 Monthly
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$972/Capacity Unit, Usage-Based
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Product Insights

  • Actionable Insights: Google Looker Studio empowers businesses to derive actionable insights from their data. It goes beyond raw data to provide meaningful, data-driven recommendations and strategies.
  • Unified Data Platform: Looker Studio offers a unified data platform that brings together data from various sources, enabling a holistic view of your organization's data. This centralization streamlines decision-making and enhances data consistency.
  • Scalable Analytics: Scalability is a key advantage of Looker Studio. Whether you're a small startup or a large enterprise, it can scale with your data needs, ensuring you have the analytics power you require as your business grows.
  • Customizable Dashboards: With Looker Studio, you can create customized dashboards tailored to your specific needs. This flexibility allows you to focus on the metrics that matter most to your organization.
  • Collaborative Environment: Collaboration is made easy with Looker Studio. Teams can work together within the platform, share insights, and collaborate on data-driven decisions, fostering a data-driven culture within your organization.
  • Real-Time Data: Stay up-to-date with real-time data insights. Looker Studio provides real-time analytics, enabling you to make informed decisions quickly and adapt to changing circumstances.
  • Enhanced Data Security: Security is a top priority, and Looker Studio offers robust data security features, including role-based access control and encryption, ensuring your data remains protected.
  • Reduced Time-to-Insight: Looker Studio's intuitive interface and powerful querying capabilities reduce the time it takes to extract valuable insights from your data, accelerating decision-making processes.
  • Optimized Performance: The platform optimizes data performance, ensuring that you can analyze large datasets efficiently, even in complex analytical scenarios.
  • Adaptive Analytics: Looker Studio adapts to changing business needs, allowing you to evolve your analytics strategy as your organization grows and your data requirements change.
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  • 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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  • Interactive Dashboards: Create dynamic, interactive dashboards that allow users to explore data, drill down into details, and gain insights effortlessly.
  • Customizable Reports: Generate tailored reports with a variety of visualization options, including charts, graphs, and tables, to communicate data findings effectively.
  • Data Exploration: Easily explore and analyze data from multiple sources with intuitive data exploration tools, making it simple to uncover hidden patterns and trends.
  • SQL-Based Queries: Leverage the power of SQL for querying and manipulating data, enabling advanced users to perform complex analyses and calculations.
  • Data Integration: Seamlessly integrate data from various platforms and sources, including databases, cloud services, and spreadsheets, for a holistic view of your organization's data.
  • Machine Learning Integration: Incorporate machine learning models and predictive analytics into your data analysis, allowing for data-driven predictions and recommendations.
  • Collaborative Workspace: Foster collaboration among team members by sharing data, insights, and reports within the platform, promoting data-driven decision-making across the organization.
  • Role-Based Access Control: Ensure data security with role-based access control, granting different levels of access to users based on their roles and responsibilities.
  • Real-Time Data Monitoring: Keep a pulse on your data with real-time data monitoring and alerts, allowing you to respond promptly to changing conditions and opportunities.
  • Scalable Architecture: Scale your analytics infrastructure as your organization grows, accommodating increasing data volumes and user demands without sacrificing performance.
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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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Product Ranking

#22

among all
Big Data Analytics Tools

#13

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 38 0 94 74 74 55 65 100 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 1074 reviews
Great User Sentiment 1173 reviews
86%
of users recommend this product

Looker Studio has a 'great' User Satisfaction Rating of 86% when considering 1074 user reviews from 3 recognized software review sites.

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.

4.4 (426)
4.2 (345)
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4.6 (19)
4.3 (365)
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4.3 (481)

Awards

SelectHub research analysts have evaluated Looker Studio and concluded it earns best-in-class honors for Reporting.

Reporting Award

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Synopsis of User Ratings and Reviews

Intuitive Interface: Users appreciate Looker Studio's user-friendly interface, making it easy to navigate and perform data analysis tasks.
Powerful Visualization: The platform offers a wide range of visualization options, enhancing data presentation and making insights more accessible.
Collaborative Tools: Users value the collaborative features, enabling teams to work together seamlessly, share insights, and drive data-driven decisions.
Real-Time Insights: Looker Studio's ability to provide real-time data insights helps users stay informed and agile in their decision-making processes.
Customization: Users can tailor dashboards and reports to their specific needs, allowing for a personalized analytics experience.
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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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Steep Learning Curve: Some users find Looker Studio challenging to learn, especially if they lack SQL or data analysis skills, leading to initial difficulties.
Data Integration Complexity: Integrating data from various sources can be complex, requiring substantial setup and maintenance efforts for certain users.
Resource Intensiveness: Resource-intensive tasks, such as processing large datasets, may lead to performance issues, causing frustration for some users.
Costs: The pricing structure can be a drawback for organizations with tight budgets, as Looker Studio's pricing may not be suitable for all user needs.
Limited Offline Functionality: Some users desire more robust offline capabilities, as Looker Studio primarily operates in an online environment.
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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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User reviews for Google Looker Studio indicate both strengths and weaknesses. Many users praise its intuitive interface, which simplifies data analysis. The platform's powerful visualization tools and real-time insights are widely appreciated, enabling users to present and act on data effectively. Collaboration features also receive positive feedback, facilitating teamwork and informed decision-making. However, several users highlight challenges. A notable drawback is the steep learning curve, especially for those without SQL or data analysis skills. Some users find data integration complex and resource-intensive, potentially impacting performance. Cost considerations also arise, with users noting that Looker Studio's pricing may not align with all budgets. In comparison to similar products, Looker Studio stands out for its user-friendly interface and strong visualization capabilities. However, some users mention limitations in offline functionality, which competitors may handle better. Overall, Google Looker Studio appears to be a valuable tool for data analysis and collaboration, but it may require a learning curve and careful consideration of budget constraints.

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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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