Apache Spark vs. MS SharePoint / SQL

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark
Score 8.6 out of 10
N/A
N/AN/A
MS SharePoint / SQL
Score 8.1 out of 10
N/A
MS SharePoint / SQL refers to Microsoft Sharepoint, a web-based collaborative platform, being used in tandem with Microsoft SQL Server to provide business intelligence analytics and reporting. They can provide BI content such as data connections, reports, scorecards, dashboards, and more.N/A
Pricing
Apache SparkMS SharePoint / SQL
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SparkMS SharePoint / SQL
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Apache SparkMS SharePoint / SQL
Top Pros
Top Cons
Features
Apache SparkMS SharePoint / SQL
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
8.9
55 Ratings
8% above category average
Pixel Perfect reports00 Ratings8.936 Ratings
Customizable dashboards00 Ratings8.753 Ratings
Report Formatting Templates00 Ratings9.145 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.1
52 Ratings
12% above category average
Drill-down analysis00 Ratings8.942 Ratings
Formatting capabilities00 Ratings9.652 Ratings
Integration with R or other statistical packages00 Ratings8.030 Ratings
Report sharing and collaboration00 Ratings9.850 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.1
56 Ratings
9% above category average
Publish to Web00 Ratings8.852 Ratings
Publish to PDF00 Ratings8.048 Ratings
Report Versioning00 Ratings8.845 Ratings
Report Delivery Scheduling00 Ratings9.740 Ratings
Delivery to Remote Servers00 Ratings10.032 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.2
34 Ratings
13% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings8.933 Ratings
Location Analytics / Geographic Visualization00 Ratings10.032 Ratings
Predictive Analytics00 Ratings10.029 Ratings
Pattern Recognition and Data Mining00 Ratings8.01 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.3
67 Ratings
8% above category average
Multi-User Support (named login)00 Ratings10.059 Ratings
Role-Based Security Model00 Ratings9.062 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings9.566 Ratings
Report-Level Access Control00 Ratings9.01 Ratings
Single Sign-On (SSO)00 Ratings9.053 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.2
57 Ratings
14% above category average
Responsive Design for Web Access00 Ratings9.754 Ratings
Mobile Application00 Ratings9.133 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings8.038 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
Apache Spark
-
Ratings
MS SharePoint / SQL
9.3
37 Ratings
16% above category average
REST API00 Ratings9.028 Ratings
Javascript API00 Ratings9.926 Ratings
iFrames00 Ratings9.027 Ratings
Java API00 Ratings9.025 Ratings
Themeable User Interface (UI)00 Ratings9.032 Ratings
Customizable Platform (Open Source)00 Ratings9.923 Ratings
Best Alternatives
Apache SparkMS SharePoint / SQL
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User Ratings
Apache SparkMS SharePoint / SQL
Likelihood to Recommend
9.9
(24 ratings)
8.8
(74 ratings)
Likelihood to Renew
10.0
(1 ratings)
8.8
(7 ratings)
Usability
10.0
(3 ratings)
9.0
(7 ratings)
Support Rating
8.7
(4 ratings)
8.7
(7 ratings)
Implementation Rating
-
(0 ratings)
7.0
(2 ratings)
User Testimonials
Apache SparkMS SharePoint / SQL
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
A simple and important scenario well suited is that you can configure alerts to notify you when the production server fails. another best feature is the report server is the central component of reporting services. For me something less appropriate is that the admin must ensure optimal performance for farm operations, they recommend that you install SQL Server on a dedicated server that does not run other farm roles and does not host databases for other applications.
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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
  • Flexible - able to make any changes we would like vs traditional service desk system.
  • ROI - We were already using SharePoint for internal intranet, so we are simply getting more use out of licensing we had already committed to.
  • Easy to use for end users.
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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
  • It is hard to setup and nightmare
  • It requires a of infrastructure, thus it could be costly because of requirement and licensing required for everything to run smoothly
  • If it is not setup and organized properly from the beginning it could be maintenance nightmare
  • It is hard to have "test" environment to do patches or similar
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Likelihood to Renew
Apache
Capacity of computing data in cluster and fast speed.
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Microsoft
This was a long-term buy-in from a corporate perspective, to remain in the SharePoint space. Migration is certainly possible, which is good for planning and having options further out. At this point, the only planned migration is to eventually move the architecture up to SharePoint/SQL 2013. At that point, we will be able to leverage some greater efficiencies, some enhanced content design and management features, and some more current social features. It is well worth a full consideration in any shop looking at a new implementation of or migration to SharePoint (although you will probably be considering 2013 versions or beyond in those discussions), but the platform should be a strong competitor to any alternatives. Realizing the capability of a fully-branded and customized website was not part of the original choice for the architecture at Lincoln, but seeing it implemented and functioning now with this capacity far beyond original expectations has certainly cemented plans to continue using it.
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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
SharePoint is very complex. This makes usability somewhat difficult from an IT perspective. An IT generalist will be able to pick it up and run with basic tasks. More customized functions would require significant specialized training and therefore limit what a standard user would be able to achieve. From an end user perspective, it's pretty straightforward to use.
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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
It's been fantastic in terms of Premier Support so far. If there is an issue and if you report if the product has an issue, they will act upon it immediately. In some cases, if you design/develop something using the platform, Microsoft appreciates it and... publishes it on their public website. But you have to wait for some time if it is a non-Premier Support issue as you may experience delays.
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Implementation Rating
Apache
No answers on this topic
Microsoft
Not implemented in best practice way, there are many customizations
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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
At the time of the two large projects, SharePoint was the enterprise solution so we were required to use that. We have since lobbied the enterprise teams to review and consider Atlassian Confluence and were successful. Confluence is cheaper than Sharepoint which is why we wanted to bring that in. The enterprise has now made Confluence an enterprise solution as an alternative to SharePoint. After using both I think SharePoint has many more add-ins than Confluence. It has much more customization ability than Confluence. SharePoint is not good for mobile readiness. Confluence is so there is a difference that might lead you to Confluence over SharePoint. I would also say that SharePoint is very document-centric and that Confluence has better KM than SharePoint does. even with the use of SQL Server. We were told that we could not use Google Drive even though it had features we liked.
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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
  • I've installed SharePoint in many different industries and each industry has seen greater collaboration among their teams both locally and nationally. The ability to collaborate more efficiently has reduced the need to have employees centrally located.
  • Companies which have used SharePoint in a end user training portal have had great ROI, since they can create the content once and share with all their users who subscribe to their training service. The web content management aspect of SharePoint is a very helpful feature.
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