Replicate vs SecretFlow
Overview
Share your Stack
Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
CLI (Node.js)
Manual
Detailed Comparison
It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works. | It is a unified framework for privacy-preserving data intelligence and machine learning. It provides an abstract device layer consists of plain devices and secret devices which encapsulate various cryptographic protocols. |
Thousands of models, ready to use;
Automatic API;
Automatic scale;
Pay by the second | Supports various privacy computing technologies and can be assembled flexibly to meet the needs of different scenarios;
Build a unified technical framework, and try to make the underlying technology iteration transparent to the upper-layer application, with high cohesion and low coupling;
Data in scenarios supported by different underlying technologies can be connected to each other |
Statistics | |
GitHub Stars - | GitHub Stars 2.6K |
GitHub Forks - | GitHub Forks 452 |
Stacks 53 | Stacks 0 |
Followers 12 | Followers 2 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Replicate, SecretFlow?
Git
Git is a free and open source distributed version control system designed to handle everything from small to very large projects with speed and efficiency.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
Mercurial
Mercurial is dedicated to speed and efficiency with a sane user interface. It is written in Python. Mercurial's implementation and data structures are designed to be fast. You can generate diffs between revisions, or jump back in time within seconds.
Presto
Distributed SQL Query Engine for Big Data
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
SVN (Subversion)
Subversion exists to be universally recognized and adopted as an open-source, centralized version control system characterized by its reliability as a safe haven for valuable data; the simplicity of its model and usage; and its ability to support the needs of a wide variety of users and projects, from individuals to large-scale enterprise operations.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
