Apache Spark vs Google Cloud Data Fusion

Apache Spark is a free, open-source engine for large-scale data analytics. It processes batches and real-time streams using Python, SQL, Scala, Java, or R. Spark SQL runs distributed ANSI SQL queries on structured tables and unstructured data such as JSON or images; MLlib provides machine-learning algorithms for local use or cluster scale. The project also describes exploratory analysis on petabyte-scale data without downsampling. Listed ecosystem components include pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg. Deployment options include standalone, Hadoop YARN, and Kubernetes. Spark runs on Windows and UNIX-like systems, including Linux and macOS, when a supported Java version is available. The 4.2.0 documentation lists Java 17, 21, or 25, Scala 2.13, Python 3.10+, and R 4.0+ (deprecated). Spark Connect separates client applications from clusters for remote access. Security is not enabled by default; Spark supports TLS for RPC connections and encryption of temporary local-disk data. The project is licensed under Apache License, Version 2.0.

Google Cloud Data Fusion is a cloud service for building and managing data pipelines that cleanse, prepare, blend, transfer, and transform data. Its visual interface lets teams design ETL and ELT pipelines without writing code. More than 150 preconfigured connectors and transformations are included at no additional cost, and lineage tracking covers datasets and individual fields for root-cause and impact analysis. It integrates with Cloud Storage, Managed Service for Apache Spark, BigQuery, and Spanner. Replication supports SQL Server, Oracle, and MySQL into BigQuery, with Datastream integration for change streams. Security integrations include IAM, Private IP, VPC Service Controls, and customer-managed encryption keys. REST APIs, schedules, triggers, logs, metrics, and dashboards support operations. Built on open-source CDAP, it supports portability across hybrid and multi-cloud environments. Basic provides 120 free pipeline-development hours monthly per account; new customers get $300 in credits. Developer costs $0.35 a month, Basic $1.80 a month, and Enterprise $4.20 a month. Execution resources are billed separately.