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Apache Spark vs SAP HANA comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

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

Categories and Ranking

Apache Spark
Average Rating
8.4
Reviews Sentiment
7.7
Number of Reviews
65
Ranking in other categories
Hadoop (1st), Compute Service (4th), Java Frameworks (2nd)
SAP HANA
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
84
Ranking in other categories
Data Virtualization (2nd), Embedded Database (4th), Relational Databases Tools (4th)
 

Featured Reviews

Ilya Afanasyev - PeerSpot reviewer
Reliable, able to expand, and handle large amounts of data well
We use batch processing. It works well with our formats and file versions. There's a lot of functionality. In our pipeline each hour, we make a copy of data from MongoDB, of the changes from MongoDB to some specific file. Each time pipeline copied all of the data, it would do it each time without changes to all of the tables. Tables have a lot of data, and in the last MongoDB version, there is a possibility to read only changed data. This reduced the cost and configuration of the cluster, and we saved about $150,000. The solution is scalable. It's a stable product.
Jayarami Reddy Pujeri - PeerSpot reviewer
Comprehensive system with real-time analytics for versatile industry applications
Our primary use case is working with various clients in industries such as pharmaceuticals and other services. We support clients as implementers of SAP HANA, providing expertise in functionality, finance, logistics, and processes The solution is very user-friendly and supports all kinds of…

Quotes from Members

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

Pros

"Spark can handle small to huge data and is suitable for any size of company."
"We use it for ETL purposes as well as for implementing the full transformation pipelines."
"The fault tolerant feature is provided."
"The solution is scalable."
"I like Apache Spark's flexibility the most. Before, we had one server that would choke up. With the solution, we can easily add more nodes when needed. The machine learning models are also really helpful. We use them to predict energy theft and find infrastructure problems."
"There's a lot of functionality."
"I feel the streaming is its best feature."
"ETL and streaming capabilities."
"The solution is easy to scale."
"We are using the solution for the DW system. The primary function of the solution is for the database in memory."
"The solution is extremely stable. That's the most important aspect of the solution, for our organization. There is no downtime, and the performance is very good."
"One feature I find very valuable, is the response time of the application on the database memory."
"It's easy to use, and the Hana Studio is pretty good."
"The in-memory computing and the efficient response time are very good features."
"Technically it resembles Oracle, but as a somewhat lighter version."
"The best feature of SAP HANA is column computing. The computing speed of the solution is also very high, so developers can easily develop programs through SAP HANA."
 

Cons

"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"When you first start using this solution, it is common to run into memory errors when you are dealing with large amounts of data."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"There were some problems related to the product's compatibility with a few Python libraries."
"Apache Spark provides very good performance The tuning phase is still tricky."
"Apache Spark could improve the connectors that it supports. There are a lot of open-source databases in the market. For example, cloud databases, such as Redshift, Snowflake, and Synapse. Apache Spark should have connectors present to connect to these databases. There are a lot of workarounds required to connect to those databases, but it should have inbuilt connectors."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"It needs a new interface and a better way to get some data. In terms of writing our scripts, some processes could be faster."
"High availability and disaster recovery are very poor in HANA."
"The solution could improve in the handling of backup data and the administration tools."
"In my limited experience using SAP, the process of granting access to different modules is difficult. Specifically, the requirement to assign roles and key codes to users rather than being able to assign them individually made the process more complex. It would be beneficial if there was a way to assign key codes separately, rather than having to create multiple roles. This would make managing access easier."
"The only downside of the product is that it is an expensive solution that needs to consider lowering its prices to improve the product."
"It is challenging to integrate it with third-party tools."
"The JDBC connectors are very slow."
"SAP HANA is a very proprietary tool and there's not as much support available for it as there is for an SQL Server (which is more popular)."
"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."
 

Pricing and Cost Advice

"Apache Spark is not too cheap. You have to pay for hardware and Cloudera licenses. Of course, there is a solution with open source without Cloudera."
"Spark is an open-source solution, so there are no licensing costs."
"Apache Spark is an open-source tool."
"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."
"The product is expensive, considering the setup."
"We are using the free version of the solution."
"Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
"On the cloud model can be expensive as it requires substantial resources for implementation, covering on-premises hardware, memory, and licensing."
"It is expensive, which isn't a problem for us because SAP HANA is processing the data so fast."
"SAP HANA is affordable. I rate it a seven out of ten."
"The price of licensing is dependent on the size of the project, however, we have found that there is scope to negotiate the cost. If the solution is implemented on-premises there may be some extra costs for hosting etc."
"Price-wise, the product falls on the higher side of the spectrum. There is no need to pay for maintenance and support additionally. Support is available for bug fixes in the product."
"The licensing could improve."
"There is an annual license to use SAP HANA."
"The price is on the expensive side, at eight out of ten, with ten being expensive."
"SAP HANA is very expensive for small to medium businesses."
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Top Industries

By visitors reading reviews
Financial Services Firm
28%
Computer Software Company
13%
Manufacturing Company
8%
Comms Service Provider
5%
Manufacturing Company
15%
Computer Software Company
12%
Financial Services Firm
10%
Government
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Spark?
We use Spark to process data from different data sources.
What is your experience regarding pricing and costs for Apache Spark?
Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...
What needs improvement with Apache Spark?
The Spark solution could improve in scheduling tasks and managing dependencies. Spark alone cannot handle sequential tasks, requiring environments like Airflow scheduler or scripts. For instance, o...
What are the biggest benefits of using SAP HANA?
Based on my work with SAP HANA, the biggest benefit that it can bring to your business is total data management. This product is by SAP - a company that serves almost all needs a client may have co...
Is SAP HANA’s customer and technical support reliable?
We have been using SAP HANA for a fairly short period of time and have only taken advantage of their customer support. So far, we have not had issues that required specialized help from technical s...
Is SAP HANA difficult to set up and start using?
SAP HANA is fairly easy to set up, however, I do not think a complete beginner can do it. You certainly need some preparation - either you need to have experience with similar solutions, or with ot...
 

Comparisons

 

Also Known As

No data available
SAP High-Performance Analytic Appliance, HANA
 

Overview

 

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
Unilever, NHS 24, adidas Group, CHIO Aachen, Hamburg Port Authority (HPA), Bangkok Airways Public Company Limited
Find out what your peers are saying about Apache Spark vs. SAP HANA and other solutions. Updated: March 2025.
845,040 professionals have used our research since 2012.