Adaptive Server Enterprise (ASE)

SAP Adaptive Server Enterprise (ASE) is the answer to all of your data management needs. To meet the rising demand for performance, reliability, and efficiency in every industry, this high-performance SQL database server drives faster, more agile online transaction processing (OLTP), on-premise or in the cloud. Much like the engine of a car, SAP ASE is a resource-efficient relational database management system (RDMS) that powers the very core of your business - data.

Modern businesses can succeed or stagnate depending on the availability of their data. Today, every business or organization has large datasets, but not all of them are able to convert their big data into ‘smart’ data. It's not about the volume of the data you are collecting - it's about the actions you take in response to that data. Without structure, purpose and insight, however, this data is meaningless and unusable. If businesses want to retrieve substantial benefits from this data, they have to turn it into actionable data.

Using ASE as a data management platform enables you to leverage the value of your data by being able to handle massive volumes of data and thousands of concurrent users by increasing the performance of your existing and future investments in data-driven business applications.

What is a relational database?

A database is simply a place to store and process structured information. Databases permit manipulation or retrieval of their contained data in usable manners. A relational database organizes data into tables according to their type or attribute, and allows for relationships to be created between data types. For example, a relational database can link data from a customer information table like the customer’s name, address and billing information, to data from a customer transaction table like product orders, based on the shared unique ID attributed to the specific customer. When a company’s order processing application submits an order to the database, the database can go to the customer order table, pull the correct information about the product order, and use the customer ID from that table to look up the customer’s billing and shipping information in the customer information table. The warehouse can then pull the correct product, the customer can receive timely delivery of the order, and the company can get paid.

Many of the documents businesses run to track inventory, sales, finance, or even perform financial projections come from a relational database operating behind the scenes.

Benefits of relational databases

A relational database allows you and your business to better understand the relationships between all available data and gain new insights for making better business decisions or identifying new opportunities. SQL (Structured Query Language), the language used to communicate with the database, includes the ability to count, add, group, and also combine queries. SQL can perform basic math and subtotal functions and logical transformations.

Relational databases have several advantages compared to other database formats, including:

Data consistency: For critical business operations like transactional processes such as bank deposits or shopping cart transactions, you need real-time updates to ensure that data is consistent across all applications and database copies so the customer can immediately see the results of the transaction they have just made and that the business workflow process can continue. Relational databases are the best at maintaining data consistency by ensuring that multiple instances of a database have the same data all the time.

Database locking and concurrency: While it is easy to update data, locking prevents other users and applications from accessing data while it is being updated. Concurrency ensures that the right access is given to users and applications according to stored policies, when multiple users or applications invoke queries at the same time.

Reduced redundancy: Relational databases eliminate data redundancy through a design technique called normalization. Normalization minimizes the duplication of information and reduces the risk of errors in data caused by copies of the same information that are not synchronized.

Ease of backup and disaster recovery: Relational databases offer easy export and import options, and backups can even be made while the database is running, making restore on failure easy. Cloud-based relational databases can even restore the loss of data measured in seconds or less.