DuckDB vs Scylla: What are the differences?

Introduction

DuckDB and Scylla are both database management systems, but they have significant differences in terms of their underlying technology, use cases, and features. In this article, we will explore the key differences between DuckDB and Scylla.

1. Storage Engine: DuckDB is an in-memory analytical database that relies on a columnar storage engine. It compresses and stores data in a column-wise fashion, which enables fast analytical queries. On the other hand, Scylla is a NoSQL database that uses log-structured merge (LSM) tree architecture for data storage. This allows for high write throughput and efficient storage of large amounts of data.

2. Data Consistency: DuckDB ensures strong consistency, which means that all data operations are immediately visible across all nodes of the database. It guarantees that a query will see the latest committed state of the data. Scylla, on the other hand, provides eventual consistency, where updates to the database may not be immediately visible, but will eventually propagate to all nodes. This enables high availability and fault tolerance.

3. Query Language: DuckDB supports SQL as its query language, making it compatible with a wide range of applications and tools that are SQL-based. It allows users to perform complex analytical queries using standard SQL syntax. In contrast, Scylla uses its own query language called CQL (Cassandra Query Language), which is similar to SQL but has some differences. CQL is specifically designed for NoSQL databases and provides features like eventual consistency and distributed querying.

4. Data Model: DuckDB follows a relational data model, where data is organized into tables and relationships are established through keys. It supports ACID transactions and provides strong data modeling capabilities. Scylla, on the other hand, follows a distributed key-value data model. It does not support ACID transactions and does not have built-in support for complex relationships. Instead, it focuses on high availability, scalability, and low latency.

5. Scalability: DuckDB is primarily designed for analytical workloads and is optimized for single-node performance. It can efficiently process complex analytical queries on a single machine. Scylla, on the other hand, is a distributed database that is built for scale. It can handle massive amounts of data and is designed to be deployed on a cluster of multiple nodes to achieve high throughput and scalability.

6. Community Support: DuckDB is an open-source project with a growing community of contributors and users. It benefits from the open-source ecosystem and the collaboration of developers worldwide. Scylla is also an open-source project with an active community, but it is more focused on providing enterprise-grade solutions and has a strong support system for commercial customers.

In summary, DuckDB and Scylla differ in their storage engine, data consistency, query language, data model, scalability, and community support. DuckDB is suited for analytical workloads with strong consistency, while Scylla is designed for high availability and scalability with eventual consistency.