During onboarding, we show how Oxla works by using real or well-known data and meaningful queries. To do this, you can choose from our ready-to-use datasets when setting up a new cluster.

Dataset Details

1) E-Commerce Transactions

  • Size: 15 GB
  • Description: A dataset simulating a high-traffic e-commerce website’s transactions.
  • Technical Evaluation: Users can assess the database’s ACID transaction compliance, indexing efficiency, join operations, and the speed of aggregate functions for sales reporting. They can also evaluate the performance of complex queries involving multiple tables and the database’s ability to handle high write-read ratios typical of e-commerce platforms.

2) Social Media Interactions

  • Size: 115 GB
  • Description: A dataset representing user activity and interactions on a social media platform, including posts, comments, user relationships, and engagement metrics.
  • Technical Evaluation: Users can check the database’s capability for text search and indexing, graph traversal queries for network connections, and real-time analytics on social engagement. The dataset is also ideal for testing the scalability of the database and its ability to handle large, unstructured data with frequent updates.

3) IoT Device Telemetry

  • Size: 45 GB
  • Description: This dataset includes time-series data from various IoT devices, with readings on environmental factors and device statuses reported at frequent intervals.
  • Technical Evaluation: The focus here is on the database’s time-series data handling, real-time query performance, and horizontal scaling. Users can test the ingestion speed of high-velocity data, the efficiency of temporal queries, and the execution of spatial queries for location-based analytics.

4) Healthcare Patient Records:

  • Size: 72 GB
  • Description: A dataset containing detailed patient records, treatment histories, diagnostic codes, billing information, and appointment schedules typical of a healthcare provider’s database.
  • Fields: PatientID, RecordID, DiagnosisCode, TreatmentCode, BillingItem, AppointmentDate, PhysicianID, TreatmentOutcome, etc.
  • Technical Evaluation: With this dataset, users can evaluate the database’s compliance with data security standards such as HIPAA, the performance of complex queries for patient history, and the effectiveness of data encryption at rest and in transit. It also allows for testing of the database’s backup and recovery processes in a sector where data integrity is critical.