The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
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Updated
Jul 11, 2023
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
ClickHouse® is a free analytics DBMS for big data
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.
An open source cybersecurity protocol for syncing decentralized graph data.
PredictionIO, a machine learning server for developers and ML engineers.
An open source time-series database for fast ingest and SQL queries
The Data Engineering Cookbook
CMAK is a tool for managing Apache Kafka clusters
A distributed, fast open-source graph database featuring horizontal scalability and high availability
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
The most widely used Python to C compiler
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.
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.
Open-Source Web UI for Apache Kafka Management
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