Data lakes have an integral part to play in the modern data-driven business environment as they provide a high degree of computing powers and storage capabilities. However, before going into the many intricacies of the SAP data lake, it is necessary to understand in some detail the concept of data lakes and what they bring to the table.
What is a Data Lake?
A data lake stores data in all thenative formats – unstructured, semi-structured. or structured. It can be easily accessed at all times and processed to arrive at analytics that helps in important business decision-making. This is what data lakes in their basic form are and the more sophisticated ones that operate on cutting-edge cloud-based technologies like the SAP data lake are capable of much more. Organizations derive multiple benefits like high performance and cost-affordable IT infrastructure when data lakes are incorporated into their systems.
There is a distinct difference between data lakes and data warehouses though people often tend to substitute one for another. Data lakes can store data in raw form before formatting while data warehouses accept data that has been cleaned, processed, and formatted to match their architecture. Further, unlike data warehouses, the structure of data lakes can vary. For example, the architecture of Snowflake data lake is quite different from the SAP data lake.
The Evolution of the SAP data lake
The SAP HANA Data Lake was launched by SAP in April 2020 to further strengthen its existing data storage capabilities and offer customers a very affordable data storage system. The features of this newly launched product consisted of an SAP HANA native storage extension as well as the SAP data lake.
From the beginning, several advanced capabilities were incorporated into the package. As a result, this relational data lake of the SAP IQ cloud-based system turned out to be no less than the then leaders in this field namely Microsoft Azure and Amazon Simple Storage Service.
Unique Structure of the SAP data lake
The unique structure of the SAP data lake resembles a pyramid with three segments – the top, middle, and bottom. Being on this platform results in increased operational efficienciesfor businesses and substantial savings in costs.
The top tier of the pyramid is reserved for data that is critical for businesses and is continually accessed and processed for daily operational requirements. This is known as hot data and the cost of storing it in the SAP data lake is the highest.
The middle of the pyramid holds what is known as warm data. It is not always used but not that insignificant to be deleted from the systems. The data is not as valuable as the top tier and hence the costs of storing are lesser.
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At the bottom of the pyramid in the SAP data lake is data that is rarely used and hence called cold data. In older storage systems where the charges were fixed regardless of the importance of the data being stored, this data would have been deleted to save on storage space and reduce costs. But in the SAP data lake, the cost of storing this data is negligible and hence businesses prefer to hold on to it for historical purposes. The tradeoff against rock-bottom prices is that access to this data is very slow.
The SAP data lake is therefore an optimized data storage service that provides support across the full lifecycle of data, from hot to warm to cold. The data tiering facility results in a significant reduction in the cost of data storage as all the data is not charged one flat fee.
Benefits of the Cloud-based SAP HANA data lake
There are several benefits of the SAP data lake making it the preferred data storage platform of top organizations around the world. What makes it more attractive is that most features help in significant cost reductions.
- One of the top-end features of the SAP data lake is the data compression facility which is at a high of 10x. It is a very appealing proposition for businesses as it dramatically reduces storage costs.
- The SAP data lake can be easily and seamlessly operated on an existing HANA Cloud or a new HANA Cloud instance. In both cases, all the attributes of the cloud environment are available such as tracking access to data, audit logging, data encryption, and unlimited storage space on demand.
- Because of the pyramid architecture of the SAP data lake, the frequently-used and hot data can be stored in quick access memory space while less-used warm and cold data can be moved to the SAP HANA Native Storage Extension (NSE) for reducing costs.
- The SAP data lake operates independently of the HANA DB and is a highly flexible storage option. Users can quickly scale up to petabytes of storage space on demand whenever required and can scale down equally fast during the slack season. Payment for storage is only for the quantum of resources used without any flat or one-time charges. This again is a highly cost-saving factor.
- Users of the SAP data lake get quick and seamless access to leading cloud providers like Amazon S3 and the Cloud Storage of Google Cloud Platform.
- High-end SAP technology is used on the SAP data lake. Hence it provides users with high-speed data ingestion as well as data analytics and is configured to be auto-deployed in the HANA Cloud.
With all these available benefits, organizations today prefer the SAP data lake platform as they not only increase operational efficiencies but also save heavily on costs.