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  5. Firebird vs Oracle

Firebird vs Oracle

OverviewDecisionsComparisonAlternatives

Overview

Oracle
Oracle
Stacks2.6K
Followers1.8K
Votes113
Firebird
Firebird
Stacks83
Followers121
Votes9
GitHub Stars1.4K
Forks263

Firebird vs Oracle: What are the differences?

Introduction

When choosing a database for your website, it is essential to consider the differences and features of various options. Firebird and Oracle are two popular database management systems, each with its own characteristics. In this article, we will outline the key differences between Firebird and Oracle, highlighting their unique qualities and functionalities.

  1. Data Types and Compatibility: Firebird supports a limited range of data types compared to Oracle. While Oracle offers a wide variety of data types to accommodate various needs, Firebird primarily focuses on the fundamental data types. This difference in support for data types can impact the compatibility and flexibility of your database.

  2. Scalability and High Availability: Oracle is known for its robust scalability and high availability features. It provides advanced clustering options, such as Real Application Clusters (RAC), which allow multiple servers to work together seamlessly. Firebird, on the other hand, has limited scalability options and may not be as suitable for extremely high-traffic or large-scale applications.

  3. Security and Authentication: Oracle provides advanced security features, including fine-grained access controls, data encryption, and comprehensive auditing capabilities. Firebird also offers security measures, but it may not have the same level of sophistication as Oracle in terms of granular access control and encryption options.

  4. Pricing and Licensing: Firebird is an open-source database system and is available free of cost, making it an attractive choice for projects with budget constraints. Oracle, on the other hand, is a commercial product that requires a license for usage. The cost of Oracle licenses can vary based on factors such as the number of processors and users, adding to the overall expenses of a project.

  5. Development Tools and Ecosystem: Oracle has a rich ecosystem of development tools, including Oracle SQL Developer, Oracle Application Express (APEX), and Oracle JDeveloper. These tools offer comprehensive features for database development, administration, and monitoring. Firebird has a smaller ecosystem of tools, but there are still options available, such as FlameRobin and IBExpert, which provide essential functionalities for Firebird database management.

  6. Community and Support: Oracle has a large user community and a dedicated support system with timely updates, patches, and documentation. Firebird also has an active community, but it may not have the same level of resources and support as Oracle. When considering the long-term maintenance and troubleshooting aspects of your database, the size and support of the community can play a significant role.

In summary, Firebird and Oracle differ in data type support, scalability and high availability options, security features, pricing and licensing, development tools and ecosystem, as well as community and support. Choosing the right database system depends on your specific requirements, budget, and the level of support and features you need for your project.

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Advice on Oracle, Firebird

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
Firebird
Firebird

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.

Firebird is a relational database offering many ANSI SQL standard features that runs on Linux, Windows, MacOS and a variety of Unix platforms. Firebird offers excellent concurrency, high performance, and powerful language support for stored procedures and triggers. It has been used in production systems, under a variety of names, since 1981.

Statistics
GitHub Stars
-
GitHub Stars
1.4K
GitHub Forks
-
GitHub Forks
263
Stacks
2.6K
Stacks
83
Followers
1.8K
Followers
121
Votes
113
Votes
9
Pros & Cons
Pros
  • 44
    Reliable
  • 33
    Enterprise
  • 15
    High Availability
  • 5
    Expensive
  • 5
    Hard to maintain
Cons
  • 14
    Expensive
Pros
  • 3
    Open-Source
  • 3
    Free
  • 1
    Easy Setup
  • 1
    Great Performance
  • 1
    Upgrade from MySQL, MariaDB, PostgreSQL
Cons
  • 2
    Speed

What are some alternatives to Oracle, Firebird?

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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