Apache Spark vs. Microsoft Access

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.

Incentivized

As a Material Purchasing/Planning/inventory tracking application, Microsoft Access serves its purpose well. It's presentation is clean, data entry is simple and the ability to customize search fields is welcome. It does, however, come with some caveats; namely, when setting search filters and the need arises to back up a step or two, with Microsoft Access you have to reset, or "clear all", adding extra steps/time to a query.

Incentivized

• Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
• Faster in execution times compare to Hadoop and PIG Latin
• Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
• Interoperability between SQL and Scala / Python style of munging data

Incentivized

• Very easy to create entity-relationship diagrams for various tables and designing mock layouts.
• Really easy to navigate as it hold[s] the classic Microsoft UI. Another good thing is that it comes with the complete MS Office Suite.
• It is really fast when joining multiple tables no matter what type of join.
• Works on pretty much same SQL scripts so no need to learn a new language!

Incentivized

• 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

Incentivized

• Microsoft Access has not really changed at all for several years. It might be nice to see some upgrades and changes.
• The help info is often not helpful. Need more tutorials for Microsoft Access to show how to do specific things.
• Be careful naming objects such as tables, forms, etc. Names that are too long can get cut off in dialog boxes to choose a table, form, report, etc. So, I wish they would have resizable dialog boxes to allow you to see objects with long names.
• I wish it could show me objects that are not in use in the database for current queries, tables, reports, forms, and macros. That way unused objects can be deleted without worrying about losing a report or query because you deleted the underlying object.

Incentivized

Capacity of computing data in cluster and fast speed.

I and the rest of my team will renew our Microsoft Access in the future because we use and maintain many different applications and databases created using Microsoft Access so we will need to maintain them in the future. Additionally, it is a standard at our place of work so it is at $0 cost to us to use. Another reason for renewing Microsoft Access is that we just don' t have the resources needed to extend into a network of users so we need to remain a single-desktop application at this time.

If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used

Incentivized

Microsoft Access is easy to use. It is compatible with spreadsheets. It is a very good data management tool. There is scope to save a large amount of data in one place. For using this database, one does not need much training, can be shared among multiple users. This database has to sort and filtering features which seem to be very useful.

Incentivized

I don't think the program has ever failed me. It is one of those programs where there is always a solution if you know where to look.

Incentivized

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.

While I have never contacted Microsoft directly for product support, for some reason there's a real prejudice against MS Access among most IT support professionals. They are usually discouraging when it comes to using MS Access. Most of this is due to their lack of understanding of MS Access and how it can improve one's productivity. If Microsoft invested more resources towards enhancing and promoting the use of MS Access then maybe things would be different.

Incentivized

there is no key idea, since it is easy to implement Microsoft Access

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.

Incentivized

Excel is a fantastic - robust application that can do so much so easily. Its easy to train and understand. However - excel does not provide a reporting function and that is typically where we will suggest a move to [Microsoft] Access. [Microsoft] Access requires a little more knowledge of data manipulation.

Incentivized

• Business leaders are able to take data driven decisions
• Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
• Business is able come up with new product ideas

Incentivized

• Not having to recreate queries or reports every time you want to use them.
• Once an item is created and saved as part of the database, you save manpower by not having to recreate them.
• ROI from a usability standpoint is great. Solid product with great functionality that requires low maintenance usually.

Incentivized