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  5. AWS Glue vs SecretFlow

AWS Glue vs SecretFlow

OverviewComparisonAlternatives

Overview

AWS Glue
AWS Glue
Stacks461
Followers819
Votes9
SecretFlow
SecretFlow
Stacks0
Followers2
Votes0
GitHub Stars2.6K
Forks452

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Detailed Comparison

AWS Glue
AWS Glue
SecretFlow
SecretFlow

A fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics.

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.

Easy - AWS Glue automates much of the effort in building, maintaining, and running ETL jobs. AWS Glue crawls your data sources, identifies data formats, and suggests schemas and transformations. AWS Glue automatically generates the code to execute your data transformations and loading processes.; Integrated - AWS Glue is integrated across a wide range of AWS services.; Serverless - AWS Glue is serverless. There is no infrastructure to provision or manage. AWS Glue handles provisioning, configuration, and scaling of the resources required to run your ETL jobs on a fully managed, scale-out Apache Spark environment. You pay only for the resources used while your jobs are running.; Developer Friendly - AWS Glue generates ETL code that is customizable, reusable, and portable, using familiar technology - Scala, Python, and Apache Spark. You can also import custom readers, writers and transformations into your Glue ETL code. Since the code AWS Glue generates is based on open frameworks, there is no lock-in. You can use it anywhere.
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
461
Stacks
0
Followers
819
Followers
2
Votes
9
Votes
0
Pros & Cons
Pros
  • 9
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Integrations
Amazon Redshift
Amazon Redshift
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS
Amazon Athena
Amazon Athena
MySQL
MySQL
Microsoft SQL Server
Microsoft SQL Server
Amazon EMR
Amazon EMR
Amazon Aurora
Amazon Aurora
Oracle
Oracle
Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
CentOS
CentOS
Ubuntu
Ubuntu
Python
Python

What are some alternatives to AWS Glue, SecretFlow?

Apache Spark

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

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

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

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

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.

Apache Flink

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.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

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