Presto vs Vertica: What are the differences?

Introduction

Presto and Vertica are two popular platforms used for data processing and analytics. While both have similar functionalities, they differ in several key aspects that make them ideal for specific use cases. In this article, we will explore six key differences between Presto and Vertica.

1. Architecture: Presto is designed as a distributed SQL query engine that operates on a cluster of machines. It follows a federated architecture, where multiple nodes work together to process queries. On the other hand, Vertica adopts a massively parallel processing (MPP) architecture, where data is divided across multiple nodes for parallel query execution.

2. Data Storage: Presto is designed to work with various data sources, including relational databases, Hadoop, and cloud storage systems like S3. It can access data in different formats, such as CSV, JSON, and Parquet. In contrast, Vertica uses its proprietary columnar storage format, optimized for efficient analytics and compression. It offers high-performance analytics on massive volumes of data.

3. Query Optimization: Presto applies optimization techniques during the query runtime to provide faster results. It uses cost-based optimization, enabling it to choose the most efficient execution plan dynamically. Vertica, on the other hand, focuses heavily on query optimization during the compilation phase. It compiles and optimizes queries in advance, resulting in faster execution for complex analytical workloads.

4. Concurrency and Scalability: Presto is designed to handle large-scale data processing with high concurrency. It scales horizontally by adding more worker nodes to the cluster, allowing it to execute queries in parallel. Vertica, on the other hand, is designed to be both concurrent and scalable. It efficiently utilizes hardware resources and supports workload management policies to prioritize different query workloads.

5. Advanced Analytics: Presto primarily focuses on providing fast and interactive SQL queries, making it an ideal choice for ad hoc analysis and exploration. It supports basic analytical functions but lacks extensive built-in support for advanced analytics like machine learning algorithms. Vertica, on the contrary, offers a wide range of built-in analytical functions and supports machine learning capabilities. It provides a comprehensive analytics platform for complex analytical workloads.

6. Cost and Licensing: Presto is open-source software with no licensing costs, making it an attractive option for organizations with limited budgets. It is maintained by a community of contributors, ensuring continuous improvement. Vertica, on the other hand, is a commercial product and requires licensing. It offers enterprise-level support and additional features that may be beneficial for organizations with specific requirements.

In summary, Presto and Vertica differ in their underlying architecture, data storage approaches, query optimization strategies, concurrency and scalability capabilities, support for advanced analytics, and cost/licensing models. Organizations should evaluate their specific requirements and use cases to choose the platform that best aligns with their needs.