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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Oracle SQL Developer
Score 7.9 out of 10
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Oracle SQL Developer is an integrated development environment (IDE) which provides editors for working with SQL, PL/SQL, Stored Java Procedures, and XML in Oracle databases.
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.
Almost all development activities (the tool is called "SQL Developer", not "DBA Toolset") can be done easily and quick with [Oracle] SQL Developer. From data model creation (tables, views) to development (creation of procedures, functions, packages) and then testing (SQL Developer includes an easy to use debugger), all tasks can be performed in a single tool.
It may not be as complete as other solutions for DBA tasks like instance monitoring, but it is usually OK for development and testing environments if you want to do some basic troubleshooting.
Object Browser in SQL Developer allows you to explore the contents of your database using the connection tree.
The SQL Worksheet is an editor that allows for execution of SQL statements, scripts, and PL/SQL anonymous blocks. SELECT statements can be executed to return results in a spreadsheet-like 'grid' or can be executed as a script such to emulate SQL*Plus behavior and output
DBA Console allows users with administrative privileges to access DBA features such as database init file configuration, RMAN backup, storage, etc.
Inability to run multiple queries on the same database. You can only run one query on a given database.
Analytical models created from complex tables isn't accurate, and needs work.
Inability to view multiple tables of a database side-by-side. When trying to find correlations between tables, it would help to be able to see them at once on the same page.
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
Oracle SQL Developer is very easy to use and there are a wide range of courses available which can help you get started just within a day. Data can be exported in multiple formats based on user requirements. Organizational data can be stored and management effectively using Oracle SQL Developer. All the data, tables, sequences, indexes can be easily created and updated in Oracle SQL Developer.
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.
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.
I have started to use Toad for Oracle recently because it is easier to sort and filter results, due to their memory sort feature that puts the results from your query in memory so that you don't have to rerun your query. I have used SQL Developer to easily update records in tables that I need to fix. I haven't found an easy way to do this in Toad other than writing SQL insert statements.
