CouchDB vs Scylla: What are the differences?

Introduction:

CouchDB and Scylla are both popular database management systems, but they have several key differences that set them apart. In this comparison, we will explore the specific distinctions between CouchDB and Scylla.

1. Data Model: CouchDB is a document-oriented database that stores data in JSON-like documents. It is schemaless, allowing flexibility in data structure. On the other hand, Scylla is a wide-column store based on Apache Cassandra, utilizing a data model that organizes data in rows, columns, and tables. It follows a schema-based approach, requiring predefined column families and column names.

2. Consistency Model: CouchDB follows eventual consistency, which means that the database may not always reflect the latest updates immediately, but it ensures that all updates will be eventually propagated. In contrast, Scylla offers strong consistency by default. It ensures that all replicas of a piece of data are consistent and up-to-date before returning a response.

3. Replication and Distribution: CouchDB uses master-master replication, allowing data to be synchronized bidirectionally across multiple instances. This enables high availability and fault tolerance. On the other hand, Scylla uses consistent hashing for data distribution and relies on peer-to-peer gossip protocol for replication. It provides linear scalability by adding more nodes to the cluster.

4. Query Language: CouchDB utilizes MapReduce as its primary query language. It allows users to define map and reduce functions to extract and manipulate data. Scylla, being based on Cassandra, uses CQL (Cassandra Query Language) for querying and manipulating data, which provides a familiar and SQL-like syntax for developers.

5. Storage Engine: CouchDB employs an append-only B-tree storage engine, where all changes are written sequentially to disk. It ensures durability and immutability of data. On the other hand, Scylla uses its own storage engine called "Seastar," which implements a log-structured merge tree (LSM) for storing and managing data efficiently.

6. Tunability and Optimal Use Case: CouchDB is often chosen when offline availability, conflict resolution, and a flexible data model are crucial requirements. It is well-suited for use cases like mobile applications and decentralized systems. Scylla, with its high throughput and low latency characteristics, is more suitable for applications that demand massive scalability, real-time analytics, and low-latency operations.

In Summary, CouchDB is a document-oriented database with eventual consistency, while Scylla is a wide-column store with strong consistency. CouchDB uses master-master replication and MapReduce, whereas Scylla utilizes consistent hashing and CQL. They have different storage engines, tunability, and ideal use cases.