What is SAP HANA?
What is SAP HANA?
SAP HANA (High-performance ANalytic Appliance) is a multi-model database that stores data in its memory instead of keeping it on a disk. The column-oriented in-memory database design allows you to run advanced analytics alongside high-speed transactions – in a single system. Why is this so important? Because it lets companies process massive amounts of data with near-zero latency, query data in an instant, and become truly data-driven. By storing data in column-based tables in main memory and bringing online analytical processing (OLAP) and online transactional processing (OLTP) together, SAP HANA is unique – and significantly faster than other database management systems (DBMS) on the market today.
Launched in 2010, SAP HANA is a modern and mature solution used by tens of thousands of customers around the world. But SAP HANA is much more than a database. In addition to acting as a database server, storing and retrieving data requested by applications, SAP HANA offers advanced search, analytics, and data integration capabilities for all types of data – structured and unstructured. It also functions as an application server and helps companies build smart, insight-driven applications based on real-time data, in-memory computing, and machine learning technology. These capabilities are available both in the cloud, and on-premise.
By combining multiple data management capabilities – and making all types of data instantly available from a single system – SAP HANA simplifies IT, helps businesses innovate, and knocks down barriers to digital transformation.
What is an in-memory database?
An in-memory database (IMDB) is a type of database that stores data in a computer’s main memory (RAM) instead of on traditional disks or solid-state drives (SSD). While most databases today have added more in-memory capabilities, they are still a disk-based storage database first. SAP HANA was built from the ground up to work with data in-memory first and leverage other storage mechanisms as necessary to balance performance and cost. Retrieval from memory is much faster than from a disk or SSD, resulting in split-second response times.
In-memory databases are often used for applications that require top speed and the ability to handle large spikes in traffic – such as telecommunications networks and banking systems. In the last 10 years or so, mainly due to advancements in multi-core processors and less expensive RAM, companies have started to use in-memory databases for a wider range of applications, including real-time analytics and predictive modeling, customer experience management, logistics, and much more.
Just how fast is SAP HANA?
faster than traditional databases
answers queries in less than 1 second
scans per second per core
aggregations per second per core
Top 10 benefits of SAP HANA
The SAP HANA database offers many more benefits than just storing data, serving it, and providing a single source of truth. The top 10 benefits of SAP HANA, both on-premises and with SAP HANA Cloud, are:
- Complete: Includes database services, advanced analytical processing, application development, and data integration
- Fast: Response to queries in less than a second in large production applications
- Versatile: Supports hybrid transactional and analytical processing and many data types
- Efficient: Provides a smaller data footprint with no data duplication, advanced compression, and reducing data silos
- Powerful: Rapidly queries large datasets with a massively parallel processing (MPP) database
- Scalable: Easily scales for data volume and concurrent users across a distributed environment
- Flexible: Deploys in a public or private cloud, in multiple clouds, on-premise, or a hybrid scenario
- Simple: Provides a single gateway to all your data with advanced data virtualization
- Intelligent: Augments applications and analytics with built-in machine learning (ML)
- Secure: Offers comprehensive data and application security, secure setup, and more
SAP HANA architecture
Built for fast queries and high-speed transactions – SAP HANA’s in-memory, column-oriented architecture also includes, database management, application development, advanced analytical processing, and flexible data virtualization.
- In-memory, columnar, massively parallel processing database: SAP HANA runs transactional and analytical workloads using a single instance of the data on a single platform. It stores data in high-speed memory, organizes it in columns, and partitions and distributes it among multiple servers. This delivers faster queries more efficiently than aggregate data and avoids costly full-table scans.
- ACID compliance: Helps ensure compliance with all requirements for Atomicity, Consistency, Isolation, and Durability (ACID) standards.
- Multi-tenancy: Allows multiple tenant databases to run in one system, sharing the same memory and processors. Each tenant database is fully isolated with its own database users, catalog, repository, data files, and log files for maximum security and control.
- Multi-tier storage and persistent memory support: Various software solutions manage multi-temperature data (hot, warm, and cold) to optimize performance and cost of storage. SAP HANA’s native storage extension is a built-in capability to intelligently manage data between memory and persistent storage such as the SAP HANA Cloud Data Lake. Learn more about SAP HANA persistent memory.
- Scaling: Supports terabytes of data in a single server and scales further by implementing a shared-nothing architecture across multiple servers in a cluster. Distributes large tables across these servers automatically based on rules.
- Data modeling: SAP HANA’s in memory technology has enabled application developers/modelers to rethink traditional modelling using a virtual data model. Graphical modelling tools enable easy collaboration between stakeholders and creation of models to execute complex business logic and data transformation that can be processed in real-time.
- Stored procedures: SAP HANA has a native language to build stored procedures and uses advanced capabilities to create complex logic that runs inside the database.
- Administration: Provides comprehensive administration tools for various platform lifecycle, performance, and management operations and automation, such as start, stop, restart, back up, and recover.
- Security: Unique real-time data anonymization capabilities to extract value from data while protecting privacy. Robust authentication, user management, and authorization protocols help ensure that users access only the data they have permission to see and handle. Learn more about SAP HANA security.
- High availability and disaster recovery: SAP HANA supports high availability and disaster recovery to meet a broad range of service levels through an array of techniques – such as backup, storage mirroring, synchronous, asynchronous, and multitarget system replication, hot standby, auto restart, and auto failover.
- SAP HANA extended application services: This is a built-in application server that enables development of services, such as REST and OData, as well as Web-based applications that can run on premises, in the cloud, and on mobile devices.
- Application lifecycle management: Helps build and package applications, transport them from development to test to production, and deploy and upgrade them.
- Application development tools: Offers lightweight development tools for data modeling and app development on-premises and in the Cloud. Alternatively, the ABAP programming language includes optimized features to build extensions to SAP applications.
- Search: Use SQL to locate text quickly across multiple columns and textual content. Run both full-text and advanced fuzzy searches for numerous languages.
- Spatial processing: SAP HANA provides native support for spatial data types and spatial functions. Spatial processing is supported by SQL through open standards to store, query, and access location-enabled content. Learn more about SAP HANA spatial processing.
- Graph: Store and process highly connected data using a property graph. Combine graph data processing with additional advanced analytical processing functionality in SAP HANA, such as text, predictive, spatial, document (JSON) and standard relational data structures.
- Streaming analytics: Store, query, and apply machine learning (ML) to streaming data to discover trends over a period. These data sources include sensors, plant equipment, and Internet of Things (IoT) devices that arrive in a time-series format.
- Data integration and replication: SAP HANA offers comprehensive features to handle all data integration scenarios. These include ETL (extract, transform, load) and ELT as well as real-time data replication, bulk-load processing, data transformation, and built-in data quality and enrichment services.
- Data federation: Perform queries on remote data sources – such as external cloud-native sources, Apache Hadoop, and other databases – in real time with data federation.
- Caching – ability to cache data to optimize federated queries against remote sources of data. Control which sources and structures this is applied to and how/when the cache is refreshed.
The history of SAP HANA
In the mid-2000s, the co-founder of SAP, Hasso Plattner, was on a mission. He wanted to develop a database that could process transactional and analytical data – and answer any business question – in real-time. 2010, SAP HANA was born and now 31,000+ direct customers run on SAP HANA today.
2010 - SAP HANA was announced and a pre-release version was shipped to select customers in November of that year. The first official version, SAP HANA 1.0, attained the first ten go-live customers.
2012 - SAP started announcing products for cloud computing with the SAP HANA Cloud PaaS (Platform-as-a-Service). SAP HANA became the fastest-growing product in SAP history with 345 customers.
2013 - The SAP HANA Enterprise Cloud (HEC) service was announced, an Infrastructure-as-a-service (IAAS) tool, that provided customers with a managed private cloud offering for SAP HANA. Now 3,000 customers and 520K+ end-users strong.
2014 - SAP sets the Guinness World’s record for largest data warehouse at 12.1 petabytes (PB). That amount could store the entire printed content of all academic research libraries (2 Petabytes) 6 times over.
2015 - Recognized as a leader by Forrester in The Forrester Wave™: In-Memory Database Platforms, Q3 2015. SAP HANA 2.0 and SAP S/4HANA ERP system written specifically for the SAP HANA platform are released, and introduce a whole new set of users to the database.
2016 - SAP HANA 2.0 general availability and launched SAP BW/4HANA data warehouse solution.
2017 - Recognized as the #1 leader in the new Forrester Wave™: Translytical Data Platforms, Q4 2017 - SAP HANA is a unified and integrated data platform that simultaneously supports many types of workloads including transactional, operational, and analytical in real-time.
2018 - Through co-innovation, SAP becomes the first major database optimized for Intel® Optane™ persistent memory
2019 - SAP HANA Cloud was announced, as SAP’s next-generation Data Platform as a Service (DPaaS). SAP HANA runs on all SAP’s hyperscaler partners’ platforms.
2020 - SAP HANA turned 10 and launched SAP HANA Cloud to deliver the next generation of innovation of SAP HANA.
The NBA created a digital fan engagement experience that tells the story of the league from the very beginning through the present day.
Goodyear is benefitting from performance improvements thanks to the SAP HANA database and migrated more than 250 SAP systems into the SAP HANA Enterprise Cloud.
Thanks to SAP HANA, Motor Oil Hellas can now better monitor equipment, as well as analyze and forecast events with greater precision.
Morocco’s Ministry of Health enabled quick and fact-based decision-making with a countrywide monitoring system based on SAP HANA.
How do you migrate from a traditional database to an in-memory and column-oriented database?
How you manage with SAP HANA is much different than in legacy databases and most implementations will result in a smaller data footprint. Dedicate time to research the technology, explore success stories, read the blogs, and develop a list of implementation resources. Here are the steps for migrating to SAP HANA:
Legacy systems always have some outdated applications, custom code, and data that must be addressed in the migration planning.
On-premises, cloud, or hybrid are all viable with SAP HANA.
Determine the amount of memory your main data set will require. Plan the memory size for static and dynamic data as well as the disk size requirements for “persistent storage.”
This is a wonderful opportunity to remove bad, duplicate, and old data to streamline your systems and reduce your data footprint.
Well ahead of your go-live date, perform a proof of concept to validate the migration process and collect feedback on what worked and what needs to be changed.
What solutions run on SAP HANA?
Many of SAP’s flagship products run on SAP HANA, below is a sample of our best-in-class solutions, powered by SAP HANA. And, our extensive network of SAP partners and customers have developed custom solutions that leverage the power of SAP HANA, to meet their specific business needs.
Run your mission-critical operations in real-time with a complete, modular cloud ERP system powered by SAP HANA, with AI and analytics capabilities.
SAP Data Intelligence
Connect to data from anywhere. Bring together data orchestration, metadata management, and powerful data pipelines with advanced machine learning.
SAP Data Warehouse Cloud
Gain valuable insights from trusted data using data integration from different sources under a common semantic layer, built on SAP HANA Cloud.
SAP Analytics Cloud
Access business intelligence, predictive and augmented analytics, and enterprise planning in a single solution - powered by SAP HANA.
SAP HANA free trial
Learn more about the SAP HANA in-memory database. Register for a demo or start your free trial today.
SAP HANA frequently asked questions
A database management system (DBMS) is software/services used for the storage and organization of data that traditionally has defined structures or formats. There are different types of DBMS systems typically classified by the type(s) of data they manage (structured data, non-structured data, etc,). A traditional ERP maintains relationships between data items, storing their basic definition and characteristics and enable data consumers to query or access information as needed.
A columnar database stores groups of related information together in columns rather than in rows. This allows for much faster queries and analysis of similar data than when using a row-based system. These databases are very common in in-memory business applications and in data warehouses where faster retrieval speed is important. The format is traditionally well suited for analytics. A columnar database reduces the amount of resources needed for queries made on related sets of data.
OLAP online analytical processing describes systems and software that are optimized for processing large amounts of data primarily for analytical purposes. This type of processing also supports complex calculations, modeling, and data mining, making it ideal for decision support and executive reporting functions.
OLTP (online transactional processing) is a computing approach that is optimized for interactive tasks that require quick response – transaction processing for point-of-sale terminals or booking reservations, for example. These tasks entail a lot of input/output interaction with users expecting instant response. OLTP does not concern itself with massive data stores beyond what is needed for the task at hand and does not involve complex computing, both of which are the domain of OLAP.
Yes. SAP HANA is a column-oriented, in-memory relational database that combines OLAP and OLTP operations into a single system. It needs less disk space than some of its competitors and is highly scalable. SAP HANA is deployable on premises, in a public or private cloud, and in hybrid scenarios. This database is suited for advanced analytical and transactional work with a variety of data types. In addition to database management, SAP HANA offers advanced analytical processing, data integration, and application development.