Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
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Microsoft Access
Score 7.6 out of 10
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Microsoft Access is a database management system from Microsoft that combines the relational Microsoft Jet Database Engine with a graphical user interface and software-development tools.
$139.99
per PC
Presto
Score 10.0 out of 10
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Presto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases.
Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.
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 …
I think Presto is one of the best solutions out there today at the cutting edge for interactive query analysis. One of the challenges is presto is a niche tool for the interactive query use case and doesn't have the knobs and whistles as much as Spark. In the foreseeable future …
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.
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.
Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
Linking, embedding links and adding images is easy enough.
Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
Organizing & design is fairly simple with click & drag parameters.
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.
Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
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
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.
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.
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.
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.
Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
