Database management systems are required to ensure good communication leading database management systems that are around us since 2008. It is exceptionally efficient as compared to many of the other counterparts because of its compatibility with sophisticated Hadoop tools. The Hadoop is a big data analysis tool and is actually the backbone of this database management system purely because, without Hadoop tools, it will not be able to deliver the value especially when it is dealing with raw data.
Hadoop has become the pre-requisite for SAP Hana Big Data Platform
With cloud computing ruling the work ecosystem everywhere, the users are enjoying the storage of data in the tunes of terabytes. The storage can be easy, but the challenge lies in the seamless extraction of the data. Hadoop shows its importance in the extraction part. Without the convenience of extraction, any big data platform can turn out to be a total failure; therefore, the Hadoop tool is important for retaining the functional viability of this database management tool.
Integrating SAP Hana big data platform with Hadoop tools is done basically to bring structure to the way data is stored and extracted. Due to the absence of structuring in the data which is the result of data storage done in various types of file types, the coherence in organization and extraction of data is missing. Thus, Hadoop has become work support that Big Data platforms need for easing the process of extraction.
Ways Hana from SAP is integrated with Hadoop
Understanding the integration process can help in making the best utilization of Hadoop in Hana’s functioning. The integration is done mainly with an aim to provide easy access to data clusters located or stored remotely. Hana Big Data platform allows setting up and installing of clusters which can be:
a. Cloud-based: It is applicable when the clusters are more than 50 in number and the data is to be accessed or exchange of information is happening between geographically wide apart locations.
b. On-premises cluster: This set-up is required when the projects are managed in specific locations. The number of nodes will be less than 50.
Thus, depending upon the type of cluster, Hadoop is integrated with Hana Smart Data.
Benefits of using Hadoop with SAP Hana
The HANA from SAP and Hadoop are making a great team in serving the users rightly. SAPUI5 on Hana is being put to use by many administrators. It is because of the Hadoop functionalities that it is embellished with.
Main benefits of integrating Hadoop with SAP Hana are:
a. Batch processing support with the convenience of raw data mining
Hadoop is an advanced big data extraction tool. Thus, it is of exceptional utility in SAP Hana applications where the requirement of seamless extraction is easily met with the help of Hadoop functionalities.
b. Cost-effective solution
Added cost-effectiveness becomes easy to achieve by integrating Hadoop with SAP’s Hana. Hadoop offers ease management of production and nonproduction databases. This varied mixture of workloads arising from different kinds of databases’ use needs the advantages of zero space reclaim, virtual positioning, and so on. Hadoop extends all these advantages and allows achieving CR at an efficiency rate of 4:1, which was 2:1 in the earlier set-up of things.
c. Fast response time
Some big data extraction tools deliver better scalability and reliability, they may not be that effective in delivering faster response time. However, every cloud’s requirements are not the same. Some may do better with high scalability or high reliability but with a slower response time. This is not the case with Hadoop. The Hadoop solutions are advised to be implemented only when the faster response time is desired.
A word of thought
Integrating Hadoop with the SAP’s Hana big data platform is not a universal panacea for all sorts of problems. The cloud-based data storage solutions users may need different kinds of issues to address. Hadoop is to be integrated only when the faster data response is required; for other value achievements, the cloud data computing using companies may employ other solutions. So, find and outline the priorities first and then implement or integrate the data extraction tool accordingly.
