Compare Apache Spark vs. SAP HANA

Apache Spark is ranked 1st in Hadoop with 11 reviews while SAP HANA is ranked 1st in Embedded Database Software with 11 reviews. Apache Spark is rated 8.0, while SAP HANA is rated 8.2. The top reviewer of Apache Spark writes "Good Streaming features enable to enter data and analysis within Spark Stream". On the other hand, the top reviewer of SAP HANA writes "We can get more tenders because of the lower cost while providing a better product or service". Apache Spark is most compared with Spring Boot, Azure Stream Analytics and AWS Lambda, whereas SAP HANA is most compared with SQL Server, Oracle Database and Oracle Database In-Memory.
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Apache Spark Logo
10,923 views|9,163 comparisons
SAP HANA Logo
10,627 views|8,733 comparisons
Most Helpful Review
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: January 2020.
397,717 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
The processing time is very much improved over the data warehouse solution that we were using.The main feature that we find valuable is that it is very fast.The features we find most valuable are the machine learning, data learning, and Spark Analytics.I feel the streaming is its best feature.The solution is very stable.The most valuable feature of this solution is its capacity for processing large amounts of data.I found the solution stable. We haven't had any problems with it.The scalability has been the most valuable aspect of the solution.

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The memory is the solution's most valuable feature. It's the main feature of HANA. Others are still the regular IT databases that are on storage and are therefore much slower than HANA. The solution is quite fast.The user interface is very good. You can do any kind of reporting analytics from the platform.The data storage requirement is reduced from the original database to the HANA database.The functionality is of the solution is very good.One feature I find very valuable, is the response time of the application on the database memory.Integration is the most valuable feature we use SAP HANA for.The most value for us was in terms of using it to issue tenders online. We host our server, but it is open to the public, so clients who want to buy those tenders were able to go online, put their tender documents up, and we could evaluate them using SAP.If you want to scale with new processes and new reports, that's fairly easy.

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Cons
I would like to see integration with data science platforms to optimize the processing capability for these tasks.We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time.We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data.When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources.The solution needs to optimize shuffling between workers.When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data.It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster.The management tools could use improvement. Some of the debugging tools need some work as well. They need to be more descriptive.

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Unlike other databases, it lacks management features that legacy databases like Oracle or SQL servers have. They need to make the solution easier to manage and offer tools that make management more effective. A lot of things you have on traditional databases you have to develop into HANA.When you do a report on a non-SAP platform, you face some compatibility problems.I think that the pricing is high and it needs improvement.The challenge right now is all databases are on S4 HANA architecture. You're running it for HANA, but not all the functionalities are available. If they can speed up getting all the databases on S4 HANA that would help.If the developers were to enhance or improve the application logic while processing the transactions, that would be great.FI, or the financial module of SAP, has room for improvement. It has to have some better localization for the Middle East, especially in regards to taxes and the letter of credit cycle. I would like to see better localization from the HCM.The interface is a little bit hard to customize. You almost have to consult the SAP original developer to change it.In terms of improvement, the speed is not as good as we thought it would be. That is why we are trying different solutions that will be built with different technologies.

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Pricing and Cost Advice
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People who are technical will accept the cost, but financially they will assess whether this solution will bring them revenue or not. People often ask, how will I profit when the cost is so high?Set up a consortium of consulting partners and hardware vendors to define your tech. Landscape TCO (total cost of ownership) and then approach the OEM for pricing (on-premise or on cloud or a hybrid model). Check if you can bring your own licenses for some of the existing application licenses on the new platform, to reduce TCO.

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Ranking
1st
out of 24 in Hadoop
Views
10,923
Comparisons
9,163
Reviews
10
Average Words per Review
309
Avg. Rating
8.0
Views
10,627
Comparisons
8,733
Reviews
11
Average Words per Review
429
Avg. Rating
8.3
Top Comparisons
Compared 35% of the time.
Compared 10% of the time.
Compared 44% of the time.
Compared 9% of the time.
Also Known As
SAP High-Performance Analytic Appliance, HANA
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SAP
Overview

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

The SAP HANA® platform helps you reimagine business by combining a robust database with services for creating innovative applications. It enables real-time business by converging trans-actions and analytics on one in-memory platform. Running on premise or in the cloud, SAP HANA untangles IT complexity, bringing huge savings in data management and empowering decision makers everywhere with new insight and predictive power.

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Sample Customers
NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi SolutionsUnilever, NHS 24, adidas Group, CHIO Aachen, Hamburg Port Authority (HPA), Bangkok Airways Public Company Limited
Top Industries
REVIEWERS
Financial Services Firm29%
Software R&D Company29%
Marketing Services Firm14%
Healthcare Company14%
VISITORS READING REVIEWS
Software R&D Company32%
Comms Service Provider12%
Media Company10%
Financial Services Firm9%
REVIEWERS
Energy/Utilities Company25%
Government13%
Construction Company13%
Wholesaler/Distributor13%
VISITORS READING REVIEWS
Software R&D Company37%
Comms Service Provider13%
Media Company6%
Retailer5%
Find out what your peers are saying about Apache, Cloudera, Hortonworks and others in Hadoop. Updated: January 2020.
397,717 professionals have used our research since 2012.
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