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What is Apache Sentry?

Apache Sentryâ„¢ is a powerful solution for implementing comprehensive role-based access control for both data and metadata in Hadoop clusters. Officially advancing from the Incubator stage in March 2016, it has gained recognition as a Top-Level Apache project. Designed specifically for Hadoop, Sentry acts as a fine-grained authorization module that allows users and applications to manage access privileges with great precision, ensuring that only verified entities can execute certain actions within the Hadoop ecosystem. It integrates smoothly with multiple components, including Apache Hive, Hive Metastore/HCatalog, Apache Solr, Impala, and HDFS, though it has certain limitations concerning Hive table data. Constructed as a pluggable authorization engine, Sentry's design enhances its flexibility and effectiveness across a variety of Hadoop components. By enabling the creation of specific authorization rules, it accurately validates access requests for various Hadoop resources. Its modular architecture is tailored to accommodate a wide array of data models employed within the Hadoop framework, further solidifying its status as a versatile solution for data governance and security. Consequently, Apache Sentry emerges as an essential tool for organizations that strive to implement rigorous data access policies within their Hadoop environments, ensuring robust protection of sensitive information. This capability not only fosters compliance with regulatory standards but also instills greater confidence in data management practices.

What is Apache Hive?

Apache Hive serves as a data warehousing framework that empowers users to access, manipulate, and oversee large datasets spread across distributed systems using a SQL-like language. It facilitates the structuring of pre-existing data stored in various formats. Users have the option to interact with Hive through a command line interface or a JDBC driver. As a project under the auspices of the Apache Software Foundation, Apache Hive is continually supported by a group of dedicated volunteers. Originally integrated into the Apache® Hadoop® ecosystem, it has matured into a fully-fledged top-level project with its own identity. We encourage individuals to delve deeper into the project and contribute their expertise. To perform SQL operations on distributed datasets, conventional SQL queries must be run through the MapReduce Java API. However, Hive streamlines this task by providing a SQL abstraction, allowing users to execute queries in the form of HiveQL, thus eliminating the need for low-level Java API implementations. This results in a much more user-friendly and efficient experience for those accustomed to SQL, leading to greater productivity when dealing with vast amounts of data. Moreover, the adaptability of Hive makes it a valuable tool for a diverse range of data processing tasks.

Media

Media

Integrations Supported

Hue
ActionIQ
Apache Iceberg
Apache Impala
Apache Kylin
Apache Zeppelin
Cloudera Data Platform
Data Virtuality
DataClarity Unlimited Analytics
IBM Cloud Mass Data Migration
IRI Data Protector Suite
MLlib
Mage Dynamic Data Masking
RazorSQL
SecuPi
Sifflet
Varada
WINDEV
lakeFS

Integrations Supported

Hue
ActionIQ
Apache Iceberg
Apache Impala
Apache Kylin
Apache Zeppelin
Cloudera Data Platform
Data Virtuality
DataClarity Unlimited Analytics
IBM Cloud Mass Data Migration
IRI Data Protector Suite
MLlib
Mage Dynamic Data Masking
RazorSQL
SecuPi
Sifflet
Varada
WINDEV
lakeFS

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

sentry.apache.org

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

Categories and Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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