Find out in this report how the two Hadoop solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
We do not feel we're getting value for the investment due to the additional resources needed for integration and maintenance.
The community support is better than the official SAP support.
We often do not know when our ticket will be handled or who is handling it, and we can wait from one to four days for a reply, which is unexpected.
Time to respond to SAP support is an issue, and finding the right person and handling the whole process are problems too.
Our operations have grown from a hundred data operations a day to as many in a couple of seconds.
There is enough scalability offered by SAP to meet our deployment needs.
The scalability rating is based on the ability to expand.
Apache Spark resolves many problems in the MapReduce solution and Hadoop, such as the inability to run effective Python or machine learning algorithms.
We recently faced customer data loss during the cluster handover or failover fallback.
We have not had any problems in the last seven to eight years.
Regarding stability, they are using legacy systems and have implemented SAP HANA.
The setup process and deployment process for SAP HANA is complex.
The main issue is the ecosystem, which lacks the widespread support that SQL enjoys.
The problem is the price; it's too expensive for what it actually delivers.
It's a recurring subscription model, which is expensive compared to legacy systems with just a maintenance fee.
SAP is not a cheap company, and its licenses are expensive.
I would rate the price for SAP HANA as high.
Not all solutions can make this data fast enough to be used, except for solutions such as Apache Spark Structured Streaming.
This architecture allows for faster data processing and real-time analytics that were not possible with traditional databases.
The concept enhances speed, allowing the database to serve and move data quickly.
One of our dashboards using Excelsius was previously developed on normal BW on Oracle data, which took 10 minutes to open. After developing the same calculation views using those tables and replacing them with calculation views in Excelsius, the dashboard opened in seconds.
Spark provides programmers with an application programming interface centered on a data structure called the resilient distributed dataset (RDD), a read-only multiset of data items distributed over a cluster of machines, that is maintained in a fault-tolerant way. It was developed in response to limitations in the MapReduce cluster computing paradigm, which forces a particular linear dataflowstructure on distributed programs: MapReduce programs read input data from disk, map a function across the data, reduce the results of the map, and store reduction results on disk. Spark's RDDs function as a working set for distributed programs that offers a (deliberately) restricted form of distributed shared memory
SAP HANA, also known as SAP High-performance Analytics Appliance, is a multi-model database that stores data in its memory, allowing users to avoid disk storage. The product combines its robust database with services for creating applications. SAP HANA is faster than other database management systems (DBMS) because it stores data in column-based tables in main memory and brings online analytical processing (OLAP) and online transaction processing (OLTP) together.
The column-oriented in-memory database design allows users to run high-speed transactions alongside advanced analytics, all in a single system. This provides companies with the ability to process very large amounts of data with low latency and query data in an instant. By combining multiple data management capabilities, the solution simplifies IT, helps businesses with innovations, and facilitates digital transformation.
The solution is structured into five groups of capabilities, categorized as:
There are three more SAP products that work alongside SAP HANA and complete the experience for users together. SAP S/4HANA Cloud is a ready-to-run cloud enterprise resource planning (ERP). SAP BW/4HANA is a packaged data warehouse, based on SAP HANA, which allows users to consolidate data across the enterprise to get a consistent view of their data. Finally, SAP Cloud is a single database as a service (DBaaS) foundation for modern applications and analytics across all enterprise data. All three products can combine with SAP HANA to deliver to users an optimized experience regarding their data.
SAP HANA Features
Each architectural group of capabilities of SAP HANA has various features that users can benefit from. These include:
SAP HANA Benefits
SAP HANA provides many benefits for its users. These include:
Reviews from Real Users
According to a database consultant at a pharma/biotech company, SAP HANA is a very robust solution with good data access.
Bruno V., owner at LAVORO AUTOM INF E COM LTDA, likes SAP HANA because the product offers advanced features, helps reduce hours, and makes it easy to find what you need.
We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.