Presto - Reading Big Data at lightning speed!

When it comes to big data analytics, processing large datasets can be a significant challenge. One of the key difficulties in this field is querying massive amounts of data efficiently, especially when dealing with complex, nested data structures.

Until now, organizations were storing huge amount of growing data in HDFS like file systems and process or read using technologies like Hive which is awfully slow or use something like Spark which is fast but may still take hours to show just one line of output. Fortunately, a new technology has emerged that aims to solve this problem: Presto.

Presto is a high-speed distributed SQL query engine designed for fast, interactive querying of large datasets. Developed by Facebook, Presto was released as an open-source project in 2013 and has since gained significant popularity in the big data community. Presto allows users to query multiple data sources with a single SQL statement, making it an ideal choice for organizations that need to analyze data from a variety of sources.

How does Presto work?

Presto is designed to run on a cluster of machines, with each node processing a portion of the data. When a user submits a query to Presto, it is broken down into smaller sub-queries, which are then distributed across the cluster for parallel processing. Presto uses a technique called pipelining to minimize data movement across nodes, ensuring that queries are executed quickly and efficiently.

One of the key features of Presto is its ability to query data in a variety of formats, including relational databases, Hadoop, and NoSQL data stores. This flexibility means that organizations can use Presto to analyze data from multiple sources, without the need for complex data integration processes.

Why use Presto?

There are several reasons why organizations might choose to use Presto:

1. Speed: Presto is designed to be fast, with query response times typically measured in seconds. This makes it ideal for interactive data analysis and ad-hoc querying.
2. Scalability: Presto is highly scalable, with the ability to query petabytes of data across thousands of nodes.
3. Flexibility: Presto can query data in a variety of formats, making it an ideal choice for organizations that need to analyze data from multiple sources.
4. Cost: Because Presto is open source, there are no licensing fees associated with its use. This can result in significant cost savings for organizations that need to process large amounts of data.
5. Community: Presto has a large and active community of users and developers, which means that there is a wealth of resources available for users who need help or want to extend the platform's functionality.

In summary, Presto is a high-speed distributed SQL query engine that is ideal for organizations that need to analyze large datasets from multiple sources. With its speed, scalability, flexibility, cost-effectiveness, and vibrant community, Presto is a powerful tool for big data analytics. If you haven't already, it's definitely worth checking out!