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Amazon RDS vs Oracle: What are the differences?
What is Amazon RDS? Set up, operate, and scale a relational database in the cloud. Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.
What is Oracle? An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism. Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
Amazon RDS and Oracle are primarily classified as "SQL Database as a Service" and "Databases" tools respectively.
"Reliable failovers" is the primary reason why developers consider Amazon RDS over the competitors, whereas "Reliable" was stated as the key factor in picking Oracle.
According to the StackShare community, Amazon RDS has a broader approval, being mentioned in 1437 company stacks & 526 developers stacks; compared to Oracle, which is listed in 106 company stacks and 92 developer stacks.
We have chosen Tibero over Oracle because we want to offer a PL/SQL-as-a-Service that the users can deploy in any Cloud without concerns from our website at some standard cost. With Oracle Database, developers would have to worry about what they implement and the related costs of each feature but the licensing model from Tibero is just 1 price and we have all features included, so we don't have to worry and developers using our SQLaaS neither. PostgreSQL would be open source. We have chosen Tibero over Oracle because we want to offer a PL/SQL that you can deploy in any Cloud without concerns. PostgreSQL would be the open source option but we need to offer an SQLaaS with encryption and more enterprise features in the background and best value option we have found, it was Tibero Database for PL/SQL-based applications.
We wanted a JSON datastore that could save the state of our bioinformatics visualizations without destructive normalization. As a leading NoSQL data storage technology, MongoDB has been a perfect fit for our needs. Plus it's open source, and has an enterprise SLA scale-out path, with support of hosted solutions like Atlas. Mongo has been an absolute champ. So much so that SQL and Oracle have begun shipping JSON column types as a new feature for their databases. And when Fast Healthcare Interoperability Resources (FHIR) announced support for JSON, we basically had our FHIR datalake technology.
In the field of bioinformatics, we regularly work with hierarchical and unstructured document data. Unstructured text data from PDFs, image data from radiographs, phylogenetic trees and cladograms, network graphs, streaming ECG data... none of it fits into a traditional SQL database particularly well. As such, we prefer to use document oriented databases.
MongoDB is probably the oldest component in our stack besides Javascript, having been in it for over 5 years. At the time, we were looking for a technology that could simply cache our data visualization state (stored in JSON) in a database as-is without any destructive normalization. MongoDB was the perfect tool; and has been exceeding expectations ever since.
Trivia fact: some of the earliest electronic medical records (EMRs) used a document oriented database called MUMPS as early as the 1960s, prior to the invention of SQL. MUMPS is still in use today in systems like Epic and VistA, and stores upwards of 40% of all medical records at hospitals. So, we saw MongoDB as something as a 21st century version of the MUMPS database.
Pros of Amazon RDS
- Reliable failovers164
- Automated backups155
- Backed by amazon130
- Db snapshots92
- Multi-availability87
- Control iops, fast restore to point of time30
- Security28
- Elastic24
- Push-button scaling20
- Automatic software patching20
- Replication4
- Reliable3
- Isolation2
Pros of Oracle
- Reliable42
- Enterprise32
- High Availability15
- Hard to maintain5
- Expensive5
- Maintainable4
- Hard to use3
- High complexity3
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Cons of Amazon RDS
Cons of Oracle
- Expensive13