Best ETL Software for Data Virtuality

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.

Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.

With an integrated product suite providing data integration, analytics, cataloging, optimization and quality, Pentaho+ enables seamless data management, driving innovation and informed decision-making. Pentaho+ has helped customers achieve a 3x increase in improved data trust, a 7x increase in impactful business results and most importantly, a 70% increase in productivity.

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

Snowplow is a best-in-class data collection platform built for Data Teams. With Snowplow you can collect rich, high-quality event data from all your platforms and products. Your data is available in real-time and is delivered to your data warehouse of choice where it can easily be joined with other data sets and used to power BI tools, custom reports or machine learning models. The Snowplow pipeline runs in your cloud account (AWS and/or GCP), giving you complete ownership of your data. Snowplow frees you to ask and answer any questions relevant to your business and use case, using your preferred tools and technologies.

Power Query is the easiest way to connect, extract, transform and load data from a wide range of sources. Power Query is a data transformation and data preparation engine. Power Query comes with a graphical interface for getting data from sources and a Power Query Editor for applying transformations. Because the engine is available in many products and services, the destination where the data will be stored depends on where Power Query was used. Using Power Query, you can perform the extract, transform, and load (ETL) processing of data. Microsoft’s Data Connectivity and Data Preparation technology that lets you seamlessly access data stored in hundreds of sources and reshape it to fit your needs—all with an easy to use, engaging, no-code experience. Power Query supports hundreds of data sources with built-in connectors, generic interfaces (such as REST APIs, ODBC, OLE, DB and OData) and the Power Query SDK to build your own connectors.