InfluxDB vs Scylla: What are the differences?

Introduction

In this article, we will discuss the key differences between InfluxDB and Scylla, two popular database management systems. Both InfluxDB and Scylla have unique features and capabilities, making them suitable for different use cases. Let's explore the differences between these two databases.

1. Data Structure: InfluxDB is a time-series database, optimized for storing and retrieving time-stamped data efficiently. It is designed to handle high write and query loads for time-based data. Scylla, on the other hand, is a NoSQL database that provides high scalability and low latency for real-time workloads. It is based on the Apache Cassandra project and is optimized for high availability and fault tolerance.

2. Consistency Model: InfluxDB follows a strong consistency model, ensuring that queries return the most up-to-date data. It provides strict consistency for both reads and writes. In contrast, Scylla uses a tunable consistency model, allowing users to choose between stronger consistency or higher availability depending on their application requirements. It provides eventual consistency by default but can be configured for stronger consistency if needed.

3. Query Language: InfluxDB uses its own query language called InfluxQL, which is specifically designed for time-series data analysis. It provides functions and operators tailored for analyzing time-based data efficiently. Scylla, on the other hand, uses Cassandra Query Language (CQL) for querying the database. CQL is a SQL-like language that supports a wide range of querying and indexing capabilities.

4. Scaling: InfluxDB provides vertical scaling, meaning it can handle increased workloads by adding more resources to a single server. It can be scaled vertically by adding more CPU, memory, or storage to the existing server. Scylla, on the other hand, provides horizontal scaling, allowing users to add more nodes to the cluster to distribute the workload. It can handle massive amounts of data and high read and write loads by adding more machines to the cluster.

5. Data Replication: InfluxDB supports continuous data replication across multiple servers to ensure high availability and fault tolerance. It uses a distributed consensus algorithm to replicate data and maintain consistency. Scylla also provides data replication for fault tolerance but uses a different approach. It uses a shared-nothing architecture where data is partitioned and replicated across multiple nodes, ensuring high availability and fault tolerance.

6. Data Model: InfluxDB uses a tag-value data model, where each data point is associated with tags and values. Tags are indexed and used for efficient filtering and grouping of data. Scylla uses a column-based data model, where data is stored in columns rather than rows. This allows for efficient read and write operations, especially when dealing with large datasets.

In summary, InfluxDB is optimized for time-series data analysis, follows a strong consistency model, and uses a tag-value data model. On the other hand, Scylla is a NoSQL database optimized for high scalability, provides tunable consistency, and uses a column-based data model. These differences make them suitable for different use cases and application requirements.