- SAP HANA
- Features of SAP HANA
- Advantages and Disadvantages of SAP HANA
- SAP HANA Architecture
- SAP HANA Use Cases
- SAP Hana Installation
- SAP Hana Studio
- SAP HANA Studio Administration Console
- How to Use SAP HANA System Monitor
- How to Use SAP HANA on Azure
- SAP HANA Modeling – Attributes, Measures, Privileges, Modeling Objects
- Data Warehousing in SAP HANA – Components, Methods, Working & Benefits
- SAP HANA Attribute View – Create Attribute View in 9 Easy Steps
- SAP HANA Analytic View
- SAP HANA Calculation View
- Tables in SAP HANA
- SAP HANA Packages
- Schema in SAP HANA
- How to Create Analytic Privileges in SAP HANA
- SAP HANA Information Composer
- Import and Export in SAP HANA
- Major Components of SAP HANA
- Reporting in SAP HANA
- SAP Bussiness Objects Reporting Tool
- create relational connection in sap hana in 8 steps/
- steps to create olap connection in sap hana/
Features of SAP HANA
It is known for its breakthrough in-memory concept that it works on. Along with it, there are many unique benefits of SAP HANA given below.
- Database Services
- Analytics and Data Processing
- Application Development and Deployment
- Data Access, Integration and Quality
- Administration and IT Operations
- An in-memory database which provides real-time transactional as well as analytical processing in high-speed i.e. both OLTP and OLAP.
- SAP HANA is fully ACID compliant. This means that the in-memory database of SAP HANA has guaranteed, secure and reliable database transactions. ACID stands for Atomicity, Consistency, Isolation, and Durability.
- Columns and partitions organize for the data stores in-memory. Data parallel process from the memory and distributed to different servers quickly.
- Multitenancy of databases is available that is, you can use more than one tenant database together as a single database and manage them individually as well.
- Multi-tier storage in the database allows the user to store data both in in-memory storage or in a disk (in columnar format).
- Predictive analysis and machine learning have been made available in SAP HANA. You can carry out high-performance and advanced predictive analysis of transactional data in real-time. Machine learning applications can be developed because SAP HANA supports R and Tensor Flow..
- With the help of advanced data streaming engines, we can do streams analysis in real-time on the event streams. Data from the event stream process and analyze. SAP HANA has a SQL-like language which uses as specially for processing data from streams.
- The data from the internet of things and sensors is also processed and analyzed in SAP HANA. This call as analyzing series data because such data fetch in a time series format. Thus, this lets the software analyze data over time like device’s energy consumption etc.
- We can do text analysis with the help of advances text algorithms used for text-mining. In SAP HANA, advanced level text analysis is done by recognizing natural-languages, subject, object, verb and doing sentiment analysis through analyzing text.
Application Development and Deployment
- In SAP HANA, applications easily developed using different tools and deployed either on-premise or on a cloud.
- Web-based application development tools are used like the SAP Web IDE, SAP HANA Studio, SAPPower Designer, SAP Enterprise Architecture Designer etc. for data managing, data modeling, administering the database and developing applications.
- Integrated application lifecycle management, one of SAP HANA features which manage the applications in building and packaging them so as for development, testing, production, deployment and upgrading. Thus, completing a lifecycle of the application.
Data Access, Integration and Quality
- Data from various sources access from or integrate into SAP HANA for analysis. The data can access and integrate either as real-time data duplication into SAP HANA or processing pre-load bulk data loads. Data adapters are applications which facilitate data integration. The adapter load data from different databases, cloud storages, Apache Hadoop.
- The data quality improves by the data cleansing. For instance, cleansing a sample of geospatial data includes removing unnecessary information from the data like names, phone numbers, street name, address, e-mail etc. Data cleansing enriches the data by improving its quality.
- The Apache Hadoop and Apache Spark integration are done by the virtue of applications like SAP Vora engine, SAP cloud platform, a big data engine, Apache Hive, Big data services, and Apache Spark adapters.
Administration and IT Operations
All the operations and functionalities of SAP HANA can administer by using different administration tools. One popularly known administration tool is SAP HANA Cockpit where you can analyse SQL execution plans, CPU functioning, memory utilization, backing-up, recovery, process execution etc.
- Security of the data in SAP HANA ensures by security approaches like single sign-on and authorization. Kerberos protocol and security assertion mark-up language (SAML) use to achieve this. All the important security aspects manage in the security section of the DBA Cockpit. Security of the data ensures by providing complete data encryption, data auditing, securing application services, data storage and communications.
- Disaster recovery will ensure in SAP HANA by native as well as third party tools. Processes used to backing-up and recovery of data if lost are mirroring, storage, backup, synchronous and asynchronous data replication etc. Using the recovery features in SAP HANA, you can keep your system at standby in various area ranges like a local campus, a city or a remote location.
SAP HANA provides a multi-engine query processing environment where different queries like textual queries, SQL queries for relational data, graph queries etc.