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Gen AI apps are built with MongoDB Atlas
The database for AI-powered applications.
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Docker image used to run data processing workloads
Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data...
Stream Processing and Complex Event Processing Engine
... to various endpoints in real time. Agile development experience with SQL-like query language and graphical drag-and-drop editor supporting event simulation. Lightweight runtime that can natively run on Kubernetes, Docker, VM, or bare metal, and embedded in any Java or Python application. Scalable, and highly available distributed event processing on Kubernetes, with NATS Streaming and Siddhi Kubernetes Operator.
... durability guarantees. Configurable replication between data centers across multiple geographic regions. Built from the ground up as a multi-tenant system. Supports isolation, authentication, authorization and quotas. Persistent message storage based on Apache BookKeeper. IO-level isolation between write and read operations. Flexible messaging models with high-level APIs for Java, Go, Python, C++, Node.js, WebSocket and C#.