Aerospike vs Scylla: What are the differences?

Aerospike vs. Scylla: Key Differences

Introduction

Aerospike and Scylla are both highly scalable NoSQL databases used for big data applications. While both offer high performance and low-latency data storage, they have key differences that distinguish them from each other.

1. Data Model: Aerospike uses a key-value data model, where each record is identified by a unique key and contains a set of bins (name-value pairs). On the other hand, Scylla is based on the Apache Cassandra data model, using a wide-column data model where data is organized into rows, columns, and column families. This allows Scylla to handle complex and dynamic data with a flexible schema.

2. Consistency Model: Aerospike provides strong consistency by default, ensuring that all replicas in a cluster are updated before acknowledging a write operation. In contrast, Scylla, like Cassandra, adopts a tunable consistency model that allows users to choose the level of consistency required for each operation. This allows for better trade-offs between latency and consistency based on specific application needs.

3. Distribution Strategy: Aerospike distributes data using a data replication strategy called "replication factor," where each record is replicated on multiple nodes. This ensures high availability and fault tolerance. On the other hand, Scylla uses a consistent hashing algorithm to distribute data across a cluster using virtual nodes. This allows for better load balancing and automatic data redistribution when nodes are added or removed from the cluster.

4. Query Language: Aerospike uses a SQL-like query language called Aerospike Query Language (AQL) to perform queries and aggregations on data. It offers a powerful set of functionalities for data manipulation. In contrast, Scylla uses Cassandra Query Language (CQL), which is based on SQL but also offers additional features specific to Cassandra's data model, such as wide-column support and secondary indexes.

5. Write Path Optimization: Aerospike optimizes the write path by storing data in memory and persisting it to disk asynchronously. This allows for extremely fast write operations and high throughput. Scylla, on the other hand, utilizes a log-structured merge (LSM) tree data structure to optimize write operations. It writes data sequentially to disk, minimizing disk I/O and enabling efficient compaction and recovery processes.

6. Community Support and Adoption: Aerospike has a dedicated and active community, with a strong focus on high-performance and low-latency use cases. Scylla, on the other hand, has gained significant traction among the developer community due to its compatibility with Apache Cassandra and its ability to handle large-scale workloads with low latencies.

In summary, Aerospike and Scylla differ in terms of their data models, consistency models, distribution strategies, query languages, write path optimization, and community support. These differences highlight the unique strengths and use cases of each database, allowing developers to choose the one that best suits their specific requirements.