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H2 Database vs Oracle: What are the differences?
Introduction
In this markdown, we will discuss the key differences between H2 Database and Oracle. H2 Database and Oracle are both popular relational database management systems (RDBMS) used for storing and managing structured data. While they serve the same purpose, there are several differences that set them apart.
Data Types Support: H2 Database supports a wide range of data types, including VARCHAR, INTEGER, BOOLEAN, BLOB, and many more. On the other hand, Oracle offers a more extensive set of data types like CLOB, RAW, TIMESTAMP, INTERVAL YEAR TO MONTH, INTERVAL DAY TO SECOND, and more.
SQL Compatibility: H2 Database offers a high level of compatibility with the SQL standard, including support for common SQL syntax and functions. Oracle, being an enterprise-level database, is known for its extensive support for SQL, including advanced features like hierarchical queries, analytic functions, and more.
Scalability and Performance: Oracle offers robust scalability and can handle large databases and high transaction loads efficiently. It provides advanced features like partitioning, clustering, and parallelism for optimal performance. On the other hand, H2 Database is more lightweight and designed for embedded or small-scale applications where scalability and performance are not the primary concern.
Administration and Maintenance: Oracle provides advanced tools and utilities for database administration, monitoring, and performance tuning. It offers features like Automatic Storage Management (ASM), Oracle Enterprise Manager, and Oracle Data Guard for high availability and disaster recovery. H2 Database, being a lightweight database, doesn't offer such extensive administration and maintenance features.
Availability and Cost: Oracle is a commercial database and requires a license for using it in production environments. It comes with comprehensive support, frequent patches, and updates. On the other hand, H2 Database is an open-source database and is freely available for use without any licensing cost. However, support and updates may be limited compared to Oracle.
Community and Ecosystem: Oracle has a large and active user community, extensive documentation, and a wide range of third-party tools and frameworks built around it. It is widely adopted and has a strong ecosystem. H2 Database, being a less popular database, may have a smaller community and limited ecosystem support.
In summary, H2 Database and Oracle differ in terms of data types support, SQL compatibility, scalability and performance, administration and maintenance features, availability and cost, as well as community and ecosystem support. Understanding these differences can help in making an informed decision while choosing a database for a specific use case.
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 H2 Database
Pros of Oracle
- Reliable44
- Enterprise33
- High Availability15
- Expensive5
- Hard to maintain5
- Maintainable4
- Hard to use4
- High complexity3
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Cons of H2 Database
Cons of Oracle
- Expensive14
