Presto and PostgreSQL

What is PostgreSQL?

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PostgreSQL is an enterprise-grade open source database management system (DBMS) that is free and offers advanced functionality common to more expensive dbmses. It is an object-relational database that supports multiple programming languages, custom data types, JSON, relational modeling, and table partitioning. Some of the companies using PostgreSQL in production include Instagram, Apple, Cisco, and Red Hat.

PostgreSQL’s wide usage and support is a result of several reasons. Being open source, the database comes for free and benefits from contributions from a wide developer community. Due to its wide usage, there are many talented and experienced people who are already conversant with it. Therefore, there is no shortage of skilled personnel who can implement and maintain data management systems powered by PostgreSQL. Features such as table partitioning, replication, and geospatial data support mean it has features normally found in closed source enterprise dbmses that are expensive to acquire and run.

PostgreSQL is highly extensible and scalable and is used to manage massive datasets reliably. Support for foreign data wrappers ensures that it integrates easily to data streams and other databases. This makes it ideal for serving as the data storage system for online analytical processing (OLAP), advanced analytics, and BI solutions. Installation is simple since it is free to download. Additionally, free docker containers and paid cloud solutions exist to support a cloud-based microservices architecture for even better horizontal scalability of the developed systems.

What Is Presto?

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Presto is a query engine used to query different data stores in differing formats in a distributed and parallel manner. It was originally developed by Facebook to manage its data warehouse developed using Apache Hive. 

Presto architecture consists of a coordinator node and multiple worker nodes. The coordinator node is responsible for accepting queries and returning results. The worker nodes do the actual computation and connect to the data stores. This distributed architecture makes Presto fast and scalable.

Leveraging PostgreSQL and Presto

Combining PostgreSQL and PrestoDB offers many benefits to developers and organizations. The advanced database features like geospatial data support, full text search, and support for different programming languages combined with being open source make it highly customizable. Developers are therefore free to configure it as they deem best for their systems. Using Presto enables better solutions as it is also highly customizable, open source, and distributed. Worker nodes can integrate easily with multiple nodes running the database as Presto ships with a free PostgreSQL plugin.

PrestoDB works by using the plugin to connect to postgreSQL. The plugin is responsible for generating SQL statements that are compatible with the database. Worker nodes use the plugins to communicate with the dbms to issue commands and fetch data. By pushing down as much work as possible to the database, Presto is able to leverage the power and features of PostgreSQL. This makes them a great combination for developing big data solutions. Some of the use cases of Presto and PostgreSQL are machine learning, data analysis, data visualization, and business intelligence.

If you’re ready to use Presto to query PostgreSQL but don’t want to worry about the complexities or overhead of managing Presto, you can use a managed service like Ahana Cloud. Ahana Cloud gives you the power of Presto without having to get under the hood. It’s a managed service for AWS and can integrate with PostgreSQL.

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