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  1. Stackups
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  3. Databases
  4. Databases
  5. Apache Derby vs Oracle

Apache Derby vs Oracle

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
Apache Derby
Apache Derby
Stacks103
Followers22
Votes0
GitHub Stars369
Forks141

Apache Derby vs Oracle: What are the differences?

## Introduction
Apache Derby and Oracle are both popular relational database management systems used in various applications and industries. However, there are key differences between the two that influence their usage and suitability for different purposes.

1. **Licensing**: One major difference between Apache Derby and Oracle is the licensing. Apache Derby is licensed under the Apache License, which allows users to freely use, modify, and distribute the software. On the other hand, Oracle database requires a commercial license for production use, which can incur significant costs for businesses.

2. **Scalability**: Oracle database is known for its robust scalability features, allowing it to handle large volumes of data and users efficiently. In comparison, Apache Derby may struggle with scalability in very large or high-demand environments, making it more suitable for smaller-scale projects.

3. **Feature Set**: Oracle database offers a wide range of advanced features such as advanced analytics, partitioning, and high availability options, making it a preferred choice for enterprise-level applications with complex requirements. Apache Derby, while feature-rich for its size, may lack some of the advanced functionalities provided by Oracle.

4. **Support and Documentation**: Oracle database has a vast community of developers and extensive official documentation, along with dedicated customer support from Oracle Corporation. Apache Derby, being an open-source project, relies more on community support and might not offer the same level of official support and documentation as Oracle.

5. **Performance**: Oracle is known for its optimized performance, especially when handling large datasets and complex queries. Apache Derby, while efficient for smaller workloads, may not offer the same level of performance optimization as Oracle in high-demand scenarios.

6. **Deployment Options**: Oracle database can be deployed on-premises, in the cloud, or in a hybrid setup, providing flexibility for organizations with varied infrastructure requirements. Apache Derby, being lightweight and embeddable, is commonly used in embedded systems or as an embedded database in applications due to its ease of deployment.

## Summary
In summary, the key differences between Apache Derby and Oracle lie in licensing, scalability, feature set, support and documentation, performance, and deployment options, influencing their suitability for different project requirements.

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Advice on Oracle, Apache Derby

Daniel
Daniel

Data Engineer at Dimensigon

Jul 18, 2020

Decided

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.

496k views496k
Comments
Abigail
Abigail

Dec 6, 2019

Decided

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.

540k views540k
Comments
Abigail
Abigail

Dec 10, 2019

Decided

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.

558k views558k
Comments

Detailed Comparison

Oracle
Oracle
Apache Derby
Apache Derby

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.

It is an open source relational database implemented entirely in Java and available under the Apache License.

-
Small footprint; Based on the Java, JDBC, and SQL standards; Provides an embedded JDBC driver
Statistics
GitHub Stars
-
GitHub Stars
369
GitHub Forks
-
GitHub Forks
141
Stacks
2.6K
Stacks
103
Followers
1.8K
Followers
22
Votes
113
Votes
0
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 5
    Expensive
Cons
  • 14
    Expensive
No community feedback yet
Integrations
No integrations available
Java
Java

What are some alternatives to Oracle, Apache Derby?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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