Awesome Data Analysis
Section: Tools · A unified model for defining both batch and streaming data-parallel processing pipelines.
FreshScore 80
Entry
Apache Beam
Appears in 6 awesome lists
Unified programming model for batch and streaming data processing. Write pipelines once, run anywhere on Flink, Spark, or Google Cloud Dataflow. Portable, extensible, and enterprise-ready for AI data pipelines. Apache 2.0 licensed.
Open github.comapache/beam
Found in these lists
Awesome HBase
Section: Integrations · Beam HBase integration.
ActiveScore 65
Awesome Integration
Section: Stream Processing · Unified programming model for batch and streaming pipelines, portable across runners such as Flink, Spark, and Google Cloud Dataflow.
FreshScore 82
Awesome Open Source AI
Section: 1. Core Frameworks & Libraries · Unified programming model for batch and streaming data processing. Write pipelines once, run anywhere on Flink, Spark, or Google Cloud Dataflow. Portable, extensible, and enterprise-ready for AI data pipelines. Apache 2.0 licensed.
FreshScore 89
Awesome Production Machine Learning
Section: Data Stream Processing · Apache Beam is a unified programming model for Batch and Streaming.
FreshScore 92
Best Of Python
Section: Beam (33 · 8.7K) - Unified programming model to define and execute data processing.. Apache-2 · (👨💻 2K · 🔀 4.7K · 📦 9.8K):
FreshScore 88
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Luigi
Python module for building complex pipelines of batch jobs. Handles dependency resolution, workflow management, visualization, and Hadoop integration. Built at Spotify and battle-tested in production. Apache 2.0 licensed.
In 15 listsDetails
Apache Airflow
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
In 13 listsDetails
Dagster
Cloud-native orchestration platform for developing and maintaining data assets including ML models. Declarative programming model with integrated lineage and observability. Apache 2.0 licensed.
In 12 listsDetails
Prefect
Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.
In 11 listsDetails
Apache Spark
Unified analytics engine for large-scale data processing. In-memory cluster computing with high-level APIs in Python, Scala, Java, and R. Powers MLlib for distributed machine learning and Structured Streaming for real-time data. Apache 2.0 licensed.
In 8 listsDetails
Kestra
Event-driven orchestration and scheduling platform for mission-critical workflows. Infrastructure-as-Code approach with declarative YAML, Git version control integration, and hundreds of plugins for data pipelines and ML workflows. Apache 2.0 licensed.
In 8 listsDetails
Apache Flink
Stream processing framework with powerful batch and streaming capabilities. High-throughput, low-latency runtime with exactly-once processing guarantees. Ideal for real-time AI inference pipelines and event-driven ML applications. Apache 2.0 licensed.
In 7 listsDetails