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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS vs Firebird

Amazon RDS vs Firebird

OverviewDecisionsComparisonAlternatives

Overview

Amazon RDS
Amazon RDS
Stacks16.2K
Followers10.8K
Votes761
Firebird
Firebird
Stacks83
Followers121
Votes9
GitHub Stars1.4K
Forks263

Amazon RDS vs Firebird: What are the differences?

Introduction

In the realm of database management systems, Amazon RDS and Firebird are two prominent options that offer various features and capabilities. Understanding the key differences between these two platforms is essential for making an informed decision on the most suitable solution for specific needs.

  1. Deployment and Management: Amazon RDS is a cloud-based service that provides automated backups, software patching, monitoring, and scaling capabilities, making it easier to set up and manage databases. On the other hand, Firebird is a self-managed relational database that requires manual intervention for tasks such as backups, patching, and scaling.

  2. Scalability: Amazon RDS offers scalable storage and compute resources, allowing users to adjust their database capacity as needed. In contrast, Firebird does not have built-in scalability features and may require manual partitioning or clustering to handle increased workloads.

  3. Cost Structure: Amazon RDS follows a pay-as-you-go pricing model based on factors like instance types, storage, and data transfer, making it more cost-effective for small to medium-sized businesses. Firebird, being open-source, is free to use but may incur costs for additional features or support services.

  4. Compatibility and Ecosystem: Amazon RDS supports multiple database engines, such as MySQL, PostgreSQL, SQL Server, and Oracle, providing users with a wide range of options for their applications. Firebird, on the other hand, is a standalone relational database with limited compatibility with other systems.

  5. Performance and Optimization: Amazon RDS offers automated performance tuning and optimization tools to improve database efficiency and response times. In comparison, Firebird requires manual optimization techniques and tuning to achieve optimal performance, which may necessitate a higher level of expertise.

  6. Security Features: Amazon RDS provides robust security features such as encryption at rest and in transit, IAM integration, and network isolation to protect sensitive data. While Firebird offers basic security measures, additional features like encryption and advanced access controls may need to be implemented manually.

In Summary, Amazon RDS excels in deployment automation, scalability, and comprehensive security features, while Firebird is a self-managed, cost-effective option with limited scalability and compatibility.

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Advice on Amazon RDS, Firebird

Phillip
Phillip

Developer at Coach Align

Mar 18, 2021

Decided

Using on-demand read/write capacity while we scale our userbase - means that we're well within the free-tier on AWS while we scale the business and evaluate traffic patterns.

Using single-table design, which is dead simple using Jeremy Daly's dynamodb-toolbox library

29.3k views29.3k
Comments

Detailed Comparison

Amazon RDS
Amazon RDS
Firebird
Firebird

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.

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.

Pre-configured Parameters;Monitoring and Metrics;Automatic Software Patching;Automated Backups;DB Snapshots;DB Event Notifications;Multi-Availability Zone (Multi-AZ) Deployments;Provisioned IOPS;Push-Button Scaling;Automatic Host Replacement;Replication;Isolation and Security
-
Statistics
GitHub Stars
-
GitHub Stars
1.4K
GitHub Forks
-
GitHub Forks
263
Stacks
16.2K
Stacks
83
Followers
10.8K
Followers
121
Votes
761
Votes
9
Pros & Cons
Pros
  • 165
    Reliable failovers
  • 156
    Automated backups
  • 130
    Backed by amazon
  • 92
    Db snapshots
  • 87
    Multi-availability
Pros
  • 3
    Free
  • 3
    Open-Source
  • 1
    Great Performance
  • 1
    Upgrade from MySQL, MariaDB, PostgreSQL
  • 1
    Easy Setup
Cons
  • 2
    Speed

What are some alternatives to Amazon RDS, 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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