1.binhnguyennus / awesome-scalability
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
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38 repositories by Attention Score · Oct 27, 2026 – Nov 2, 2026 (UTC)
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
ClickHouse® is a real-time analytics database management system
Apache Spark - A unified analytics engine for large-scale data processing
All-in-one IoT Platform - Device management, data collection, processing and visualization.
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.
Cloud-native OSS search engine for observability
A distributed, fast open-source graph database featuring horizontal scalability and high availability
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Apache Beam is a unified programming model for Batch and Streaming data processing.
An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
The most widely used Python to C compiler
An open source cybersecurity protocol for syncing decentralized graph data.
Seamless multi-primary syncing database with an intuitive HTTP/JSON API, designed for reliability
The Data Engineering Cookbook
Apache DataFusion Ballista Distributed Query Engine
Arkime is an open source, large scale, full packet capturing, indexing, and database system.
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
The Open Source Feature Store for AI/ML
The official home of the Presto distributed SQL query engine for big data
Open-Source Web UI for Apache Kafka Management
Hazelcast is a unified real-time data platform combining stream processing with a fast data store, allowing customers to act instantly on data-in-motion for real-time insights.
Simple and Distributed Machine Learning Python Library porting ML algorithms for Spark
Apache Ignite
Open source security data lake for threat hunting, detection & response, and cybersecurity analytics at petabyte scale on AWS
One advanced and mature open-source MPP (Massively Parallel Processing) database. Open source alternative to Greenplum Database.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
大数据入门指南 :star:
A graph database that supports more than 100+ billion data, high performance and scalability (Include OLTP Engine & REST-API & Backends)
A crazy fast analytical database, built on bitmaps. Perfect for ML applications. Learn more at: http://docs.featurebase.com/. Start a Docker instance: https://hub.docker.com/r/featurebasedb/featurebase
Distributed Big Data Orchestration Service
GraphFrames is a package for Apache Spark which provides DataFrame-based Graphs
ADAM is a genomics analysis platform with specialized file formats built using Apache Avro, Apache Spark, and Apache Parquet. Apache 2 licensed.
Low-code tool for automating actions on real time data | Stream processing for the users.
Multi-Modal Database replacing MongoDB, Neo4J, and Elastic with 1 faster ACID solution, with NetworkX and Pandas interfaces, and bindings for C 99, C++ 17, Python 3, Java, GoLang 🗄️
High-performance, time-indexed object storage for robotics and industrial IoT
Big Data essentials: Hadoop, MapReduce, Spark. Explore tutorials and demos in Jupyter notebooks—most are self-contained and live, ready to run with a click.