Apache Spark vs. Microsoft BI (MSBI)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 8.7 out of 10
N/A
N/AN/A
Microsoft BI (MSBI)
Score 8.4 out of 10
N/A
Microsoft BI is a business intelligence product used for data analysis and generating reports on server-based data. It features unlimited data analysis capacity with its reporting engine, SQL Server Reporting Services alongside ETL, master data management, and data cleansing.
$9.99
per user/per month
Pricing
Apache SparkMicrosoft BI (MSBI)
Editions & Modules
No answers on this topic
Power BI Pro
$9.99
per user/per month
Power BI Premium
4,995
per month
Offerings
Pricing Offerings
Apache SparkMicrosoft BI (MSBI)
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Features
Apache SparkMicrosoft BI (MSBI)
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
8.6
49 Ratings
5% above category average
Pixel Perfect reports00 Ratings9.042 Ratings
Customizable dashboards00 Ratings8.049 Ratings
Report Formatting Templates00 Ratings9.047 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
8.7
49 Ratings
8% above category average
Drill-down analysis00 Ratings9.044 Ratings
Formatting capabilities00 Ratings8.049 Ratings
Integration with R or other statistical packages00 Ratings9.039 Ratings
Report sharing and collaboration00 Ratings9.049 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
9.0
48 Ratings
8% above category average
Publish to Web00 Ratings9.044 Ratings
Publish to PDF00 Ratings9.044 Ratings
Report Versioning00 Ratings9.040 Ratings
Report Delivery Scheduling00 Ratings9.043 Ratings
Delivery to Remote Servers00 Ratings9.024 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
9.0
48 Ratings
11% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.047 Ratings
Location Analytics / Geographic Visualization00 Ratings9.044 Ratings
Predictive Analytics00 Ratings9.042 Ratings
Pattern Recognition and Data Mining00 Ratings9.01 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
9.0
49 Ratings
5% above category average
Multi-User Support (named login)00 Ratings9.046 Ratings
Role-Based Security Model00 Ratings9.043 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings9.046 Ratings
Report-Level Access Control00 Ratings9.01 Ratings
Single Sign-On (SSO)00 Ratings9.028 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
8.5
39 Ratings
7% above category average
Responsive Design for Web Access00 Ratings8.036 Ratings
Mobile Application00 Ratings8.027 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings9.936 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
Apache Spark
-
Ratings
Microsoft BI (MSBI)
8.8
21 Ratings
11% above category average
REST API00 Ratings9.019 Ratings
Javascript API00 Ratings9.019 Ratings
iFrames00 Ratings9.018 Ratings
Java API00 Ratings9.017 Ratings
Themeable User Interface (UI)00 Ratings9.018 Ratings
Customizable Platform (Open Source)00 Ratings8.017 Ratings
Best Alternatives
Apache SparkMicrosoft BI (MSBI)
Small Businesses

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Score 9.7 out of 10
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Score 9.9 out of 10
Enterprises
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Score 8.8 out of 10
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User Ratings
Apache SparkMicrosoft BI (MSBI)
Likelihood to Recommend
9.9
(24 ratings)
8.7
(73 ratings)
Likelihood to Renew
10.0
(1 ratings)
8.0
(25 ratings)
Usability
10.0
(3 ratings)
8.9
(14 ratings)
Availability
-
(0 ratings)
9.5
(2 ratings)
Performance
-
(0 ratings)
7.0
(2 ratings)
Support Rating
8.7
(4 ratings)
8.9
(15 ratings)
In-Person Training
-
(0 ratings)
6.9
(3 ratings)
Online Training
-
(0 ratings)
8.5
(2 ratings)
Implementation Rating
-
(0 ratings)
9.6
(7 ratings)
Configurability
-
(0 ratings)
10.0
(2 ratings)
User Testimonials
Apache SparkMicrosoft BI (MSBI)
Likelihood to Recommend
Apache
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
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Microsoft
Microsoft BI is well suited for Stream analytics, easy data integration, report creation and UI/UX designs (limited but what all available are great ones) Microsoft BI may be less appropriate for handling huge number of datasets and difficult queries. It may also be difficult for a company with heavy data.
Read full review
Pros
Apache
  • Apache Spark makes processing very large data sets possible. It handles these data sets in a fairly quick manner.
  • Apache Spark does a fairly good job implementing machine learning models for larger data sets.
  • Apache Spark seems to be a rapidly advancing software, with the new features making the software ever more straight-forward to use.
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Microsoft
  • Comparatively easy to use compared to other data analytics solutions, collaborating with other colleagues on data work is simple.
  • Using Visual Studio for database, ETL, reporting, and analytics development save time and money.
  • Transfer of data from one application to another via Excel and comparison of data attributes between applications
  • Dashboard functionality, as well as Python support, are available, allowing you to add additional charts and graphs.
Read full review
Cons
Apache
  • Memory management. Very weak on that.
  • PySpark not as robust as scala with spark.
  • spark master HA is needed. Not as HA as it should be.
  • Locality should not be a necessity, but does help improvement. But would prefer no locality
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Microsoft
  • The race to perfect gathering of Non-Traditional datasets is on-going; with Microsoft arguably not the leader of the pack in this category.
  • Licensing options for PowerBI visualizations may be a factor. I.e. if you need to implement B2C PowerBI visualizations, the cost is considerably high especially for startups.
  • Some clients are still resistant putting their data on the cloud, which restricts lots of functionality to Power BI.
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Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
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Microsoft
Microsoft BI is fundamental to our suite of BI applications. That being said, Northcraft Analytics is focused on delighting our customers, so if the underlying factors of our decision change, we would choose to re-write our BI applications on a different stack. Luckily, mathematics are the fundamental IP of our technology... and is portable across all BI platforms for the foreseeable future.
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Usability
Apache
The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.
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Microsoft
The Microsoft BI tools have great usability for both developers and end users alike. For developers familiar with Visual Studio, there is little learning curve. For those not, the single Visual Studio IDE means not having to learn separate tools for each component. For end-users, the web interface for SSRS is simple to navigate with intuitive controls. For ad-hoc analysis, Excel can connect directly to SSAS and provide a pivot table like experience which is familiar to many users. For database development, there is beginning to be some confusion, as there are now three tool choices (VS, SSMS, Azure Data Studio) for developers. I would like to see Azure Data Studio become the superset of SSMS and eventually supplant it.
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Reliability and Availability
Apache
No answers on this topic
Microsoft
The product has been reliable.
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Performance
Apache
No answers on this topic
Microsoft
SQL Server Reporting Services (SSRS) can drag at times. We created two report servers and placed them under an F5 load balancer. This configuration has worked well. We have seen sluggish performance at times due to the Windows Firewall.
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Support Rating
Apache
1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
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Microsoft
While support from Microsoft isn't necessarily always best of breed, you're also not paying the price for premium support that you would on other platforms. The strength of the stack is in the ecosystem that surrounds it. In contrast to other products, there are hundreds, even thousands of bloggers that post daily as well as vibrant user communities that surround the tool. I've had much better luck finding help with SQL Server related issues than I have with any other product, but that help doesn't always come directly from Microsoft.
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In-Person Training
Apache
No answers on this topic
Microsoft
This training was more directed toward what the product was capable of rather than actual programming.
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Online Training
Apache
No answers on this topic
Microsoft
I have used on-line training from Microsoft and from Pragmatic Works. I would recommend Pragmatic Works as the best way to get up to speed quickly, and then use the Microsoft on-line training to deep dive into specific features that you need to get depth with.
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Implementation Rating
Apache
No answers on this topic
Microsoft
We are a consulting firm and as such our best resources are always billing on client projects. Our internal implementation has weaknesses, but that's true for any company like ours. My rating is based on the product's ease of implementation.
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Alternatives Considered
Apache
All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional type programming easily based on the situation. Also it doesn't need special data ingestion or indexing pre-processing like Presto. Combining it with Jupyter Notebooks (https://github.com/jupyter-incubator/sparkmagic), one can develop the Spark code in an interactive manner in Scala or Python
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Microsoft
We have used the built in ConnectWise Manager reports and custom reports. The reports provide static data. PowerBI shows us live data we can drill down into and easily adjust parameters. It's much more useful than a static PDF report.
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Return on Investment
Apache
  • Faster turn around on feature development, we have seen a noticeable improvement in our agile development since using Spark.
  • Easy adoption, having multiple departments use the same underlying technology even if the use cases are very different allows for more commonality amongst applications which definitely makes the operations team happy.
  • Performance, we have been able to make some applications run over 20x faster since switching to Spark. This has saved us time, headaches, and operating costs.
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Microsoft
  • As a SaaS provider we see being able to provide self-service BI to our client users as a competitive advantage. In fact the MSSQL enabled BI is a contributing factor to many winning RFPs we have done for prospective client organisations.
  • However MSSQL BI requires extensive knowledge and skills to design and develop data warehouses & data models as a foundation to support business analysts and users to interrogate data effectively and efficiently. Often times we find having strong in-house MSSQL expertise is a bless.
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ScreenShots