MariaDB vs Scylla: What are the differences?

Introduction

This article provides a comparison between MariaDB and Scylla, highlighting the key differences between the two database management systems.

1. Query Language:

   MariaDB uses SQL (Structured Query Language) as its query language, which is a standardized language for managing relational databases. On the other hand, Scylla uses CQL (Cassandra Query Language), which is a SQL-like language specifically designed for use with the Cassandra database. While SQL is more widely known and supported, CQL has specific features that make it optimized for distributed systems like Scylla.

2. Data Model:

   MariaDB follows a relational data model, where data is organized into structured tables with rows and columns. It supports ACID (Atomicity, Consistency, Isolation, Durability) properties and has built-in support for foreign key constraints. In contrast, Scylla follows a NoSQL data model, specifically a wide-column store based on Cassandra, where data is stored as key-value pairs in rows with flexible schemas. Scylla does not support ACID properties and does not have built-in support for foreign keys, as it is designed for high scalability and low latency in distributed environments.

3. Replication and Clustering:

   MariaDB supports both master-slave and master-master replication, allowing for high availability and data redundancy. It also provides clustering options like Galera Cluster for synchronous replication. Scylla, on the other hand, is built for distributed environments right from the start. It has a peer-to-peer architecture and is based on a shared-nothing model, where each node in the cluster is independent and self-sufficient. Replication in Scylla is achieved through the automatic partitioning and distribution of data across multiple nodes for scalability and fault tolerance.

4. Performance:

   MariaDB is known for its performance and stability in traditional database applications. It is well-suited for complex queries and high transactional workloads. Scylla, on the other hand, is designed for big data applications that require high throughput and low latency. It can handle massive amounts of data and scale horizontally by adding more nodes to the cluster. Scylla leverages the power of SSDs (Solid State Drives) and high-performance networks to achieve exceptional performance in distributed environments.

5. Indexing:

   MariaDB provides various indexing options like B-tree indexes, hash indexes, and full-text indexes to optimize query performance based on different use cases. Scylla, being a wide-column store, uses a built-in secondary index that allows efficient querying on columns other than the primary key. Additionally, Scylla makes use of an in-memory index combined with SSTable (Sorted String Table) storage format for faster data retrieval.

6. Data Durability and Availability:

   MariaDB ensures data durability through various mechanisms like write-ahead logging, data replication, and crash recovery. It provides features like point-in-time recovery and automatic backups for data protection. Scylla, being designed for high availability and fault tolerance, achieves data durability by automatically replicating data across multiple nodes in the cluster. It also provides tunable consistency levels, allowing trade-offs between availability and data consistency.

In summary, MariaDB is a relational database management system with a strong focus on ACID compliance and SQL support, while Scylla is a NoSQL database designed for high scalability, low latency, and distributed environments with a SQL-like querying language (CQL).