Best ETL Software for SQL

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.

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.

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.

Etlworks is a modern, cloud-first, any-to-any data integration platform that scales with the business. It can connect to business applications, databases, and structured, semi-structured, and unstructured data of any type, shape, and size. You can create, test, and schedule very complex data integration and automation scenarios and data integration APIs in no time, right in the browser, using an intuitive drag-and-drop interface, scripting languages, and SQL. Etlworks supports real-time change data capture (CDC) from all major databases, EDI transformations, and many other fundamental data integration tasks. Most importantly, it really works as advertised.

Stop wasting time managing your own integrations or fighting the limitations of black-box "solutions". Instantly use data from any source in your app, in the format that works best for you. 500+ API & DB sources, connector SDK, OAuth flows, flexible data models, instant vector embeddings, managed transactional & analytical storage, and instant SQL, REST & GraphQL APIs. Arch lets you build AI-powered features on top of your customer’s data without having to worry about building and maintaining bespoke data infrastructure just to reliably access that data.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.

TROCCO is a fully managed modern data platform that enables users to integrate, transform, orchestrate, and manage their data from a single interface. It supports a wide range of connectors, including advertising platforms like Google Ads and Facebook Ads, cloud services such as AWS Cost Explorer and Google Analytics 4, various databases like MySQL and PostgreSQL, and data warehouses including Amazon Redshift and Google BigQuery. The platform offers features like Managed ETL, which allows for bulk importing of data sources and centralized ETL configuration management, eliminating the need to manually create ETL configurations individually. Additionally, TROCCO provides a data catalog that automatically retrieves metadata from data analysis infrastructure, generating a comprehensive catalog to promote data utilization. Users can also define workflows to create a series of tasks, setting the order and combination to streamline data processing.

Find out why the heavy hitters are using the Crux external data automation platform to scale external data integration, transformation, and observability without increasing headcount. Our cloud-native data integration technology accelerates the ingestion, preparation, observability and ongoing delivery of any external dataset. The result is that we can ensure you get quality data in the right place, in the right format when you need it. Leverage automatic schema detection, delivery schedule inference, and lifecycle management to build pipelines from any external data source quickly. Enhance discoverability throughout your organization through a private catalog of linked and matched data products. Enrich, validate, and transform any dataset to quickly combine it with other data sources and accelerate analytics.