Introduction

Background

At Oxla, we offer preloaded sample datasets as a feature of our SaaS platform. These datasets allow users to easily test our solution with practical examples from various use cases.

Datasets in the Onboarding Flow

On the first login or during onboarding, users can use our custom “Create Cluster” form. It simplifies the initial setup and allows you to create your first cluster with sample datasets.

This form includes the data storage setup and showcases pre-existing datasets available for testing so you can quickly access and play around with the sample data.

After onboarding, you can still access the demo datasets upon Data Storage creation to explore different options.

Datasets Overview

Check out how our database works in real-life cases with the sample data we provide. The datasets include:

1) eCommerce

This dataset is suitable to explore sales trends, customer behaviour, and product performance to inform business decisions.

• Size: 16.41 GB.
• Technical Evaluation: This dataset consists of 4 tables related to transactions such as orders, parts, suppliers, and customers. It is ideal for evaluating Oxla’s capability to manage complex join queries for analytics, assessing its efficiency in indexing, performing joins, and calculating sales aggregates.

2) Web Traffic

Filtering, aggregation, and joins for analyzing web traffic logs and user interactions.

• Size: 16.6 GB
• Technical Evaluation: This dataset enables analysis by providing filtered data, ensuring smooth parsing and loading. It provides use cases for queries such as log analysis and event processing.

3) Urban Mobility

Access data for in-depth analysis of urban mobility trends and scalability.

• Size: 41.07 GB
• Technical Evaluation: Real-time data from New York’s taxi service, demonstrating the use case for Urban Mobility. This dataset focuses on resource optimization through Oxla queries.

4) Social Media

This dataset contains records of activity and events published by social media users.

• Size: 528.93 MB
• Technical Evaluation: This dataset represents user activity and interactions, including posts, comments, user relationships, and engagement metrics. It helps analyze and understand user behaviour and online trends.