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Articles
  • Articles
  • GET STARTED
    • Core Concepts
      • Core Components
      • Deployment Models
      • Entities Overview
      • Upsolver Timeline
      • Schema Detection and Evolution
    • Pipeline Basics
    • Understanding Sync and Non-Sync Jobs
  • DATA
    • Optimization Processes for Iceberg Tables in Upsolver
    • Column Case Sensitivity
    • Column Transformations
    • Compaction Process
    • Expectations
    • Field Name Encoding
    • Iceberg Adaptive Clustering
    • Schema Evolution
      • Iceberg Schema Evolution
      • Snowflake Schema Evolution
      • Redshift Schema Evolution
    • System Columns
    • Working with Date Patterns
  • JOBS
    • Ingest Data Using CDC
      • Performing Snapshots
      • MySQL Binlog Retention
      • PostgreSQL Partitioned Tables
      • CDC Known Limitations
    • Transformation
      • Flattening Arrays
      • Working with Arrays
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  1. GET STARTED

Core Concepts

Last updated 6 months ago

Upsolver is a cloud data pipeline engine that ingests data from a wide variety of sources and then aggregates, filters, and processes the data for the target platform. Upsolver performs these tasks quickly and efficiently thanks to its unique architecture.

This section introduces the following fundamental concepts you must understand to use Upsolver effectively:

Core Components
Deployment Models
Entities Overview
Upsolver Timeline
Schema Detection and Evolution