Collaborative Data Science Using Mode SQL And Presto

Ahana Cloud for Presto is a SaaS Managed Service which speeds up the performance of leading business intelligence, data visualization, and SQL tools like Mode SQL.

Mode SQL In A Minute

Mode is a modern collaborative data science platform meant to help data scientists with diverse skillsets work effectively both individually and as a team. By supporting the use of SQL, Python, and R, Mode SQL enables users to use the language they are most comfortable working with or combine them as needed. Support for multiple users helps teams collaborate on projects and increases productivity. Created by Mode Analytics, it is an online platform meant to offer simplicity, power, and versatility to data scientists and analysts. This has resulted in more than 50% of the Fortune 500 companies using the platform. Some firms using Mode include VMWare, Bloomberg, Everlane, InVision, and Reddit.

Mode SQL

Among the products the platform offers is the Mode SQL Editor, which uses SQL to carry out data analysis online and to share the results with business users. To be able to use the platform, one either registers for the free plan that supports 5 users or the business or enterprise plans that offer more features, handle larger volumes of data, and support more users. Users provide connections to the data store they wish to use from the various databases supported. 

image from mode.com

Data scientists and analysts then create definitions and run queries against the connected database. Advanced logic like looping and logic statements can be added through Liquid. The results are used to create reports and dashboards using Mode chart builder or piped to notebooks for further analysis. Workspaces, member management, and report management can be handled programmatically through APIs. Combined with support for multiple databases, these features greatly simplify the data science workflow. Some of the data stores Mode SQL support include MariaDB, PostgreSQL, TimescaleDB, Snowflake, Vertica, Redshift, and Presto.

Why Use Presto

Using Presto increases the performance of the developed solutions due to its massively parallel processing (MPP) architecture. It enables users to process big data efficiently and improves response times. The use of SQL greatly reduces the entry barrier for beginners. This enables users to carry out analysis and gain valuable insights from the data faster, improving productivity and performance.

Data Science With Mode SQL and Presto

The Mode platform can be combined with the Presto query engine to provide users with a high-performance stack for developing custom data science solutions. Presto is able to federate many databases, providing both a virtualized data lake and access to more data sources than Mode connects to. Therefore, users have access to all their data in a centralized place which they can connect to using Mode SQL as Presto supports SQL. Results of the query can be processed with more powerful languages offering features absent in SQL on the platform using Liquid, Python, and/or R.

To use Mode SQL with Presto, one needs to have a presto database server/cluster running. One then connects to the database instance and writes SQL queries against it. The results of the queries are saved and used to build dashboards and reports to be accessed by end-users.

Ahana Cloud is the cloud-native SaaS managed service for Presto, see how you can turbocharge Mode in 30 minutes!

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