Overview

Firebird

Stacks83

Followers121

Votes9

GitHub Stars1.4K

Forks263

ScyllaDB

Stacks143

Followers197

Votes8

Firebird vs Scylla: What are the differences?

# Introduction
This Markdown code compares the key differences between Firebird and Scylla databases, highlighting the specific distinctions between the two database management systems.

1. **Architecture**: Firebird is a relational database management system (RDBMS) that follows a client-server architecture, where the server is responsible for managing data storage and processing queries. In contrast, Scylla is a distributed NoSQL database that utilizes a shared-nothing architecture, allowing for horizontal scalability and high availability by distributing data across multiple nodes.

2. **Data Model**: Firebird uses a traditional relational data model with support for SQL queries, tables, and relationships, making it suitable for transactional applications that require ACID compliance. On the other hand, Scylla employs a wide-column store data model based on Apache Cassandra, optimized for handling large amounts of data with high throughput and low latency, making it ideal for big data and real-time analytics applications.

3. **Consistency and Availability**: Firebird prioritizes data consistency, ensuring that all reads and writes return the most recent data, which may impact availability in case of network partition or node failure. In contrast, Scylla focuses on high availability by sacrificing strict consistency in favor of eventual consistency, allowing reads to return data that may not be the most recent, providing uninterrupted access to data even during failures.

4. **Indexing**: Firebird supports various traditional indexing methods like B-trees and hash indexes to optimize query performance for relational operations, while also providing full-text search capabilities. On the other hand, Scylla utilizes distributed partitioned secondary indexes (DPSI) to efficiently query data using non-primary keys, enhancing performance in distributed environments at the cost of increased storage requirements.

5. **Language Support**: Firebird primarily supports SQL as its query language, with minimal support for procedural language extensions like stored procedures and triggers using PSQL (Procedural SQL). In contrast, Scylla does not natively support SQL but provides a CQL (Cassandra Query Language) interface for data manipulation, leveraging Apache Cassandra's query language for managing distributed databases efficiently.

6. **Ecosystem and Community**: Firebird has a smaller ecosystem and community compared to Scylla, which benefits from the backing of the Apache Software Foundation and a large open-source community actively contributing to its development and support, providing resources and plugins for various use cases and integrations.

In Summary, the key differences between Firebird and Scylla databases lie in their architecture, data model, consistency, availability, indexing methods, language support, and ecosystem/community size, making each database suitable for different types of applications and environments.

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Advice on Firebird, ScyllaDB

Tom

CEO at Gentlent

Jun 9, 2020

Decided

The Gentlent Tech Team made lots of updates within the past year. The biggest one being our database:

We decided to migrate our #PostgreSQL -based database systems to a custom implementation of #Cassandra . This allows us to integrate our product data perfectly in a system that just makes sense. High availability and scalability are supported out of the box.

387k views387k

Comments

Vinay

Head of Engineering

Sep 19, 2019

Needs advice

The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.

The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.

174k views174k

Comments

Detailed Comparison

Firebird	ScyllaDB
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.	ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows.
-	High availability; horizontal scalability; vertical scalability; Cassandra compatible; DynamoDB compatible; wide column; NoSQL; lightweight transactions; change data capture; workload prioritization; shard-per-core; IO scheduler; self-tuning
Statistics
GitHub Stars 1.4K	GitHub Stars -
GitHub Forks 263	GitHub Forks -
Stacks 83	Stacks 143
Followers 121	Followers 197
Votes 9	Votes 8
Pros & Cons
Pros 3 Free 3 Open-Source 1 Great Performance 1 Easy Setup 1 Upgrade from MySQL, MariaDB, PostgreSQL Cons 2 Speed	Pros 2 Replication 1 High performance 1 Written in C++ 1 High availability 1 Scale up
Integrations
No integrations available	KairosDB Wireshark JanusGraph Grafana Hackolade Prometheus Kubernetes Datadog Kafka Apache Spark

What are some alternatives to Firebird, ScyllaDB?

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

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

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

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 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

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 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

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.