Apache Spark vs Materialize

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.

Materialize is a live data layer for apps and AI agents that uses SQL to create up-to-the-second views. Rather than rebuilding query results from scratch as data arrives, it updates them incrementally. Connected sources appear as continually updating tables with sub-second freshness. SQL features include multi-way, lateral, and outer joins, recursive SQL, and SUBSCRIBE, which streams query-result changes over a standard Postgres connection.

Materialize is wire-compatible with PostgreSQL and supports clients and tools that work with PostgreSQL. Listed integrations include PostgreSQL, MySQL, SQL Server, CockroachDB, Kafka, Model Context Protocol, dbt, and webhooks such as EventBridge and Segment. Transformed updates can go to downstream systems including Kafka and Apache Iceberg. It is available as managed Cloud, self-managed Kubernetes software, and a Docker-based local development Emulator. The free self-managed Community Edition is limited to 24 GiB memory and 48 GiB disk. Cloud On-Demand is $1.50 a month, with usage-based compute, storage, and networking; Cloud Capacity is $1.50 a year, with storage and networking billed separately.