DataByte

DataByte is a managed Data Engineering and operations platform designed to handle Data Ingestion, Transformation, Analytics, Governance, and Machine Learning through a unified interface. The platform is built for Cloud-Native environments and supports No-Code and Low-Code pipeline development.

The platform is structured into several functional modules:

• The Data Ingester module supports ingestion from Databases, APIs, File Systems, and Cloud Storage. It utilizes three distinct methods: Batch Pipelines, Change Data Capture (CDC) for real-time synchronization, and Advanced ETL using a library of over 1,000 connectors.
• The Transformers module provides a Spark-powered environment for orchestrating Distributed ETL Pipelines. The system features Intelligent Scheduling, auto-scaling on Kubernetes, and Dynamic Resource Allocation.
• The Algorithm module provides six specific capabilities: Sherlock for root cause analysis, Anomaly Detector for real-time deviation monitoring, and Forecaster for time-series predictions using 25 algorithms. It also includes ProcBot for automated script execution, Data Insider for API Publishing over enterprise datasets, and ML Studio for the Machine Learning lifecycle.
• The Analytics module enables data exploration through Visual Queries, Dashboards, and Custom Reports with scheduled delivery across Web, Mobile, and Email channels.
• The Data Catalog provides centralized Metadata Management, including Lineage Tracking, Automated Discovery, and Governance Policy enforcement.
• The DataOps module provides real-time Pipeline Observability, SLA Tracking, and Resource Utilization Monitoring.

DataByte supports deployment on-premises, in Hybrid Environments, or on public cloud platforms including AWS, GCP, and Azure.