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CockroachDB vs Oracle: What are the differences?
Key Differences between CockroachDB and Oracle
CockroachDB and Oracle are both popular database management systems, but they have several key differences:
1. Architecture: CockroachDB is built upon a distributed and horizontally scalable architecture, while Oracle follows a traditional client-server architecture. This means that CockroachDB can handle high volumes of data and traffic more efficiently by distributing the data across multiple nodes, whereas Oracle relies on a single server for data storage.
2. Scalability: CockroachDB is designed to scale out easily by adding more nodes to the cluster, allowing it to handle increasing workloads as the data grows. On the other hand, Oracle requires more complex scaling methods, such as adding more servers or partitioning the data, which can be time-consuming and challenging.
3. Consistency Model: CockroachDB uses a strict linearizable consistency model, which ensures that every read operation returns the most up-to-date value. Oracle, on the other hand, offers several consistency levels, including eventual consistency, offering flexibility but potentially sacrificing strict consistency.
4. ACID Compliance: CockroachDB guarantees full ACID compliance, ensuring the reliability and integrity of the data. Oracle also supports ACID properties, but the level of support may vary depending on the configuration and settings.
5. Deployment Options: CockroachDB supports both on-premises and cloud-based deployments, allowing flexibility in choosing the infrastructure. Oracle is traditionally deployed on-premises, although it also offers cloud solutions through Oracle Cloud.
6. Cost: CockroachDB is an open-source database, which means it is free to use for most use cases. Oracle, on the other hand, is a commercial database that requires licensing, making it more costly for organizations.
In summary, CockroachDB and Oracle differ in their architectural design, scalability options, consistency models, ACID compliance, deployment options, and cost.
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 CockroachDB
Pros of Oracle
- Reliable44
- Enterprise33
- High Availability15
- Expensive5
- Hard to maintain5
- Maintainable4
- Hard to use4
- High complexity3
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Cons of CockroachDB
Cons of Oracle
- Expensive14
