A data lake is a storage option for all types of data. Data accessed from this repository can be examined and analyzed to make data-based decisions, a critical need in the present data-driven business environment. However, data lakes today are more than just a repository, they meet all the challenges of data management.
Data is growing exponentially in petabyte levels and becoming more complex, mainly due to the number of sources like applications, various formats, IoT, and social media. Data lakes always take these factors in their stride and hence implementing a modern one like SAP data lake helps organizations improve performance, lower costs, and gain more access and insights to data.
Where does SAP Data Lake Fit in the Data Architecture
To understand where SAP data lake fits into the data tier, visualize data architecture as a pyramid.
At the top of the pyramid is the data that is most critical for your business and has to be accessed frequently and often immediately. It is also the most valuable for you and is known as hot data stored in-memory. Hence, this data is operationally most expensive.
At the bottom of the pyramid is the raw data that is less used and cannot be accessed as quickly as the top tier. The trade-off against the speed of operations is that large amounts of data can be accessed for a low price.
In the middle of the pyramid is the important SAP data lake. In the past, this segment would be typically treated as cold storage but not now with the SAP HANA data. This relational database structure optimizes simplification and acceleration of data analysis and can rapidly access massive volumes of data too.
In a nutshell, this cloud-based SAP data lake helps to manage data through a reasonable life cycle. Critical and urgent data is available in real or near-real-time as is older data. This tiering in the form of a pyramid helps to keep costs down and you can choose how to store your data based on how quickly and frequently you need to access it.
What is Cloud-based SAP HANA data lake
In April 2020, SAP announced HDL (HANA Data Lake) as a component of its cost-effective cloud services. It offers cost-effective storage options including SAP HANA native storage extension and a built-in relational SAP data lake. You have the advantage of keeping current and business-critical (hot) data in memory for real-time processing while transferring data that is used frequently but not daily (warm) to the SAP HANA Native Storage Extension (NSE). Further, for old data which is still important for you, use the HANA Data Lake (IQ) and get access to it whenever required. This tiering of data provides the opportunity to decide where you want to store the data based on when you need it, thereby reducing costs.
The SAP data lake is a relational data lake which in effect means that the SAP IQ database is deployed in the cloud and provides processing capabilities at par with Azure or Amazon Web Service. It also offers 10x excellent compression of existing data, greatly saving storage costs. The data lake can also store both structured and unstructured data and the SAP data lake can be enabled either in the current HANA Cloud instance or maximized in a new HANA Cloud instance. In both systems, more storage space can be added at any time. Other typical cloud-based data lake features like security, encryption of data, audit logging, and tracking of data access are available too.
Features of SAP HANA Data Lake
Several high-performing features of SAP HANA data lake makes it a preferred option for organizations around the world.
- Based on SAP IQ technology
- Highly elastic and works independently of HANA DB. It can scale up to petabytes of data on-demand, enabling businesses to avoid investing in hardware and software for any additional need for resources.
- Provides seamless access to cloud storage like Amazon Web Service S3 and Google Cloud Platform Cloud Storage.
- Excellent high-performing ability to analyze data
- Provisioned to automatically complement and be administered with HANA Cloud
- Enabled for high-speed ingestion.
These cutting-edge features of SAP data lake result in a host of benefits for businesses.
Benefits of SAP HANA data lake
- Enabling ingestion of any type of data, both structured and unstructured form on-premises or cloud data sources
- Low Total Cost of Ownership (TCO) which is a financial estimate to help you decide the direct and indirect cost of the SAP data lake
- Easy to configure and use (single access layer in HANA Cloud)
- Columnar architecture enabling smooth and fast analytic processing
Finally, given all these features and benefits, which typical customers stand to gain the most from the SAP data lake
Distinctive Use Cases
- Those who are using SAP HANA on-premise can choose to exercise the right to use HANA Cloud as a hybrid option
- Customers who need a cost-effective and high-performing data lake solution.
- Organizations migrating database management to the cloud from on-premises systems.
- Businesses going through increased demand for data volumes but do not have the resources to immediately invest in hardware and software.
- Users desiring cost-effective storage capabilities without facing any lag or drop in performance.
Summing up, SAP data lake provides excellent and affordable data lake solutions and fast access to data whenever needed.