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Apache Spark
What it is
Apache Spark is a free engine for large-scale data analytics. It processes batch data and real-time streams using Python, SQL, Scala, Java, or R. Spark SQL runs distributed ANSI SQL queries over structured tables and unstructured data such as JSON or images. MLlib provides machine-learning algorithms for local use or cluster deployment. The project describes support for exploratory analysis of petabyte-scale data without downsampling. Its listed ecosystem includes 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 such as 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 supports remote connections between client applications and clusters. Security features are not enabled by default, though Spark supports TLS for RPC and encryption of temporary local-disk data. The project is licensed under Apache License, Version 2.0.
For and against
For
- Processes batches and real-time streams.
- Spark SQL supports distributed ANSI queries.
- MLlib algorithms can scale to clusters.
- Deployment options include Kubernetes and Hadoop YARN.
- Free plan; Apache License, Version 2.0.
Against
- Security features are not enabled by default.
- R 4.0+ is listed as deprecated.
- Requires a supported Java version.
The verdict
Apache Spark combines distributed SQL, streaming, and machine-learning capabilities in one analytics engine. Plan for security configuration and check the documented runtime requirements before deployment.
Who it suits
Spark suits teams and developers working with large-scale analytics, batch jobs, or real-time streams. It may also fit data science workflows that use its listed languages and ecosystem integrations.
Plans and prices
Apache Spark
Open-source distributed data analytics engine · download, PyPI, Maven Central, and Docker options
Read 30 Sep 2026 · spark.apache.org
On the record
- Batch and streaming
- Spark processes data in batches and real-time streams using Python, SQL, Scala, Java, or R.spark.apache.org · read 30 Sep 2026
- Client connectivity
- Spark Connect separates client applications from Spark clusters and supports remote connectivity.spark.apache.org · read 30 Sep 2026
- Data science
- The project says Spark supports exploratory data analysis on petabyte-scale data without downsampling.spark.apache.org · read 30 Sep 2026
- Deployment
- Spark documents standalone, Hadoop YARN, and Kubernetes deployment options.spark.apache.org · read 30 Sep 2026
- Encryption
- Spark supports TLS encryption for RPC connections and encryption of temporary data written to local disks.spark.apache.org · read 30 Sep 2026
- Integrations
- The listed ecosystem includes pandas, TensorFlow, PyTorch, scikit-learn, Apache Kafka, Kubernetes, Delta Lake, and Apache Iceberg.spark.apache.org · read 30 Sep 2026
- License
- The project website states Apache Spark is licensed under the Apache License, Version 2.0.spark.apache.org · read 30 Sep 2026
- Machine learning
- MLlib provides machine-learning algorithms that can run locally and scale to clusters.spark.apache.org · read 30 Sep 2026
- Operating systems
- Spark runs on Windows and UNIX-like systems, including Linux and macOS, where a supported Java version is available.spark.apache.org · read 30 Sep 2026
- Purpose
- Apache Spark is a unified engine for large-scale data analytics.spark.apache.org · read 30 Sep 2026
- Release and runtime requirements
- The 4.2.0 documentation lists Java 17, 21, or 25, Scala 2.13, Python 3.10+, and R 4.0+ (deprecated).spark.apache.org · read 30 Sep 2026
- Security
- Security features such as authentication are not enabled by default, and the documentation says deployments are not secure by default.spark.apache.org · read 30 Sep 2026
- SQL
- Spark SQL executes distributed ANSI SQL queries and supports structured tables and unstructured data such as JSON or images.spark.apache.org · read 30 Sep 2026
- Support
- The project directs users to mailing lists and community resources for help.spark.apache.org · read 30 Sep 2026
