Aerospike vs Elasticsearch: What are the differences?

Introduction

Aerospike and Elasticsearch are two popular database systems used for different purposes. While Aerospike is a high-performance NoSQL database, Elasticsearch is a distributed search and analytics engine. Here are the key differences between these two technologies:

1. Data Model:

Aerospike follows a key-value data model, where data is stored and retrieved based on a primary key. On the other hand, Elasticsearch utilizes a document-oriented data model, where data is stored in JSON-like documents and can be queried using full-text search.

2. Search Capabilities:

While both Aerospike and Elasticsearch offer search capabilities, Elasticsearch is designed specifically for searching and achieving high speeds in searching large volumes of data. It supports advanced search features like fuzzy search, autocomplete, and search across multiple fields. Aerospike, on the other hand, focuses more on high-performance data processing rather than search functionalities.

3. Scalability:

Both Aerospike and Elasticsearch are designed to be scalable, but they handle scalability in different ways. Aerospike uses a shared-nothing architecture, where data is distributed and replicated across multiple nodes. It offers automatic data partitioning and replication, making it horizontally scalable. Elasticsearch, on the other hand, uses a distributed architecture with a cluster of nodes. It allows for horizontal scaling by adding more nodes to the cluster and automatically redistributes data across the nodes.

4. Consistency and Durability:

Aerospike guarantees strong consistency and durability by default. It ensures that all nodes in the cluster agree on the state of data and provides various options for durability, including synchronous replication. Elasticsearch, on the other hand, focuses more on availability and eventual consistency. It allows for distributed system failures by providing configurable consistency levels and relies on eventual consistency for performance optimization.

5. Data Replication and Backup:

Aerospike offers multi-node data replication and automatic data backup, ensuring data availability and recovery in case of node failures. Elasticsearch also supports data replication and backup, but it provides additional features like snapshot and restore, which allow taking incremental backups and restoring data even across different clusters.

6. Use Cases:

Aerospike is commonly used in applications requiring low-latency or real-time data processing, such as real-time bidding, fraud detection, and recommendation systems. Elasticsearch, on the other hand, is widely used for full-text search, log analysis, and data analytics, especially in applications dealing with large volumes of textual data.

In summary, Aerospike is a high-performance NoSQL database with a key-value data model, while Elasticsearch is a distributed search and analytics engine with a document-oriented data model. Aerospike focuses more on data processing performance, strong consistency, and durability, while Elasticsearch excels in search capabilities, scalability, and handling large volumes of textual data.