Apache Hive

Apache Hive

Apache Software Foundation
+
+

Related Products

  • HiveMQ
    91 Ratings
    Visit Website
  • Google Cloud BigQuery
    2,027 Ratings
    Visit Website
  • DbVisualizer
    585 Ratings
    Visit Website
  • AnalyticsCreator
    46 Ratings
    Visit Website
  • Planview ProjectAdvantage
    121 Ratings
    Visit Website
  • SCIKIQ
    14 Ratings
    Visit Website
  • Semarchy xDM
    64 Ratings
    Visit Website
  • TIMi
    68 Ratings
    Visit Website
  • ActiveBatch Workload Automation
    375 Ratings
    Visit Website
  • ChatD&B
    Visit Website

About

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

About

PySpark is an interface for Apache Spark in Python. It not only allows you to write Spark applications using Python APIs, but also provides the PySpark shell for interactively analyzing your data in a distributed environment. PySpark supports most of Spark’s features such as Spark SQL, DataFrame, Streaming, MLlib (Machine Learning) and Spark Core. Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrame and can also act as distributed SQL query engine. Running on top of Spark, the streaming feature in Apache Spark enables powerful interactive and analytical applications across both streaming and historical data, while inheriting Spark’s ease of use and fault tolerance characteristics.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and anyone looking for a data warehouse software that facilitates reading, writing, and managing large datasets using SQL

Audience

Application development solution for DevOps teams

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5
features 4.0 / 5
design 5.0 / 5
support 5.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Pros & Cons from Real Users

Pros

  • Open Source Easy to learn - similar to SQL Fast performance Various data structures supported Scalable to meet growing demands Integrates with various tools & databases

Cons

  • Needs more SQL functionalities like subqueries & better optimization for advanced query like joins.

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Software Foundation
Founded: 1999
United States
hive.apache.org

Company Information

PySpark
spark.apache.org/docs/latest/api/python/

Alternatives

Apache Drill

Apache Drill

The Apache Software Foundation

Alternatives

Apache HBase

Apache HBase

The Apache Software Foundation
Apache Hudi

Apache Hudi

Apache Corporation
Apache Sentry

Apache Sentry

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
Spark Streaming

Spark Streaming

Apache Software Foundation

Categories

Categories

Integrations

Apache Spark
Fosfor Decision Cloud
Apache Phoenix
Ascend
Baidu Sugar
Captain Compliance
CelerData Cloud
Dataiku
Hue
IBM Cloud Pak for Integration
Lyftrondata
Mage Dynamic Data Masking
Okera
Omniscope Evo
SAS Studio
Secoda
Syntho
Timbr.ai
lakeFS

Integrations

Apache Spark
Fosfor Decision Cloud
Apache Phoenix
Ascend
Baidu Sugar
Captain Compliance
CelerData Cloud
Dataiku
Hue
IBM Cloud Pak for Integration
Lyftrondata
Mage Dynamic Data Masking
Okera
Omniscope Evo
SAS Studio
Secoda
Syntho
Timbr.ai
lakeFS
Claim Apache Hive and update features and information
Claim Apache Hive and update features and information
Claim PySpark and update features and information
Claim PySpark and update features and information