Best ETL Software for Azure Data Factory

BigQuery is an ideal tool for Extract, Transform, Load (ETL) processes, enabling businesses to automate data ingestion, transformation, and loading for analytics. It allows users to transform raw data into useful formats using SQL queries and integrates with various ETL tools to streamline workflows. The platform’s scalability ensures that ETL jobs run smoothly, even with vast amounts of data. New users can take advantage of the $300 in free credits to explore BigQuery’s ETL capabilities and experience the seamless processing of data for analytics. With its high-performance query engine, BigQuery ensures that ETL processes are fast and efficient, regardless of data size.

Simplify ETL pipeline creation with AnalyticsCreator’s automation capabilities, increasing efficiency in pipeline creation and management. Generate reliable, high-quality code for platforms like SSIS, Azure Data Factory, etc. to streamline data movement across your ecosystem. Support diverse data transformations, including cleansing, enrichment, and aggregations, for structured and unstructured data. Manage connections to multiple data sources and targets, including databases, data lakes, and cloud platforms, improving visibility through automated lineage tracking. Empower your team with version control and agile methodologies, ensuring better adaptability and collaboration across workflows. Optimize your ETL processes with CI/CD compatibility for maximum flexibility.

Ascend gives data teams a unified and automated platform to ingest, transform, and orchestrate their entire data engineering and analytics engineering workloads, 10X faster than ever before.​ Ascend helps gridlocked teams break through constraints to build, manage, and optimize the increasing number of data workloads required. Backed by DataAware intelligence, Ascend works continuously in the background to guarantee data integrity and optimize data workloads, reducing time spent on maintenance by up to 90%. Build, iterate on, and run data transformations easily with Ascend’s multi-language flex-code interface enabling the use of SQL, Python, Java, and, Scala interchangeably. Quickly view data lineage, data profiles, job and user logs, system health, and other critical workload metrics at a glance. Ascend delivers native connections to a growing library of common data sources with our Flex-Code data connectors.