MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
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SQL Developer
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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.
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Pricing
MongoDB
Oracle SQL Developer
Editions & Modules
Shared
$0
per month
Serverless
$0.10million reads
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Dedicated
$57
per month
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Offerings
Pricing Offerings
MongoDB
SQL Developer
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Fully managed, global cloud database on AWS, Azure, and GCP
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Community Pulse
MongoDB
Oracle SQL Developer
Considered Both Products
MongoDB
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SQL Developer
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Chose Oracle SQL Developer
I've used TOAD before, but I like SQL Developer more. It's better in every aspect. When it comes to UI, easy of use, features, it's better and more advanced compared to TOAD.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
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.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
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.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
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.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
At times, Oracle SQL Developer may experience freezing issues. However, despite this occasional inconvenience, the tool offers valuable features such as the ability to integrate plugins like utPLSQL, which greatly assists in debugging and testing our packages. Additionally, the usage of breakpoints and the flexibility to format text according to individual configurations enhance the debugging process.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
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.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB
