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Known for its speed and ease of use, Apache Spark is a powerful tool for data engineering. Its in-memory data processing capabilities and extensive libraries make it a favorite for big data processing.
Apache Kafka is a distributed event streaming platform that facilitates real-time data streaming and processing. It's widely used for building data pipelines and supporting real-time analytics.
Amazon Simple Storage Service (S3) is a highly scalable and cost-effective object storage service. It's often used to store and retrieve large volumes of data in the cloud.
Google BigQuery is a fully managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google's infrastructure. It's a popular choice for data warehousing.
Apache NiFi is an open-source data integration tool that provides an intuitive user interface for designing data flows and automating data movement.
AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it simple to prepare and load data for analytics. It's particularly valuable for working with data in the AWS ecosystem.
Databricks Delta Lake is an open-format storage layer that brings ACID transactions to Apache Spark and big data workloads. It simplifies data engineering workflows, making data quality and reliability a priority.
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. It's often used for orchestrating complex data pipelines.
Snowflake is a cloud-based data warehousing platform that provides a powerful environment for data storage, processing, and analysis.
Azure Data Factory is a cloud-based data integration service that allows you to create data-driven workflows for orchestrating and automating data movement and data transformation.
Dbt is an open-source command-line tool that enables data analysts and engineers to transform data in their warehouse more effectively.
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