Average Ratings 1 Rating

Total
ease
features
design
support

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Apache Hive is a data warehouse solution that enables the efficient reading, writing, and management of substantial datasets stored across distributed systems using SQL. It allows users to apply structure to pre-existing data in storage. To facilitate user access, it comes equipped with a command line interface and a JDBC driver. As an open-source initiative, Apache Hive is maintained by dedicated volunteers at the Apache Software Foundation. Initially part of the Apache® Hadoop® ecosystem, it has since evolved into an independent top-level project. We invite you to explore the project further and share your knowledge to enhance its development. Users typically implement traditional SQL queries through the MapReduce Java API, which can complicate the execution of SQL applications on distributed data. However, Hive simplifies this process by offering a SQL abstraction that allows for the integration of SQL-like queries, known as HiveQL, into the underlying Java framework, eliminating the need to delve into the complexities of the low-level Java API. This makes working with large datasets more accessible and efficient for developers.

Description

Palo empowers businesses to swiftly establish a PB-level MPP architecture data warehouse service in just minutes while seamlessly importing vast amounts of data from sources like RDS, BOS, and BMR. This capability enables Palo to execute multi-dimensional big data analytics effectively. Additionally, it integrates smoothly with popular BI tools, allowing data analysts to visualize and interpret data swiftly, thereby facilitating informed decision-making. Featuring a top-tier MPP query engine, Palo utilizes column storage, intelligent indexing, and vector execution to enhance performance. Moreover, it offers in-library analytics, window functions, and a range of advanced analytical features. Users can create materialized views and modify table structures without interrupting services, showcasing its flexibility. Furthermore, Palo ensures efficient data recovery, making it a reliable solution for enterprises looking to optimize their data management processes.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Doris Yes 
Apache Spark Yes 
SQL Yes 
Algonomy Yes 
Apache Avro Yes 
Apache Iceberg Yes 
Apache Ranger Yes 
Apache Zeppelin Yes 
Baidu Sugar Yes 
Ema Yes 
IBM Cloud Pak for Integration Yes 
Jotform Yes 
LT Browser Yes 
Mage Static Data Masking Yes 
RATH Yes 
Secoda Yes 
Timbr.ai Yes 
Varada Yes 
Xtendlabs Yes 

Integrations

Apache Doris Yes 
Apache Spark Yes 
SQL Yes 
Algonomy No 
Apache Avro No 
Apache Iceberg No 
Apache Ranger No 
Apache Zeppelin No 
Baidu Sugar No 
Ema No 
IBM Cloud Pak for Integration No 
Jotform No 
LT Browser No 
Mage Static Data Masking No 
RATH No 
Secoda No 
Timbr.ai No 
Varada No 
Xtendlabs No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

hive.apache.org

Vendor Details

Company Name

Baidu AI Cloud

Founded

2000

Country

China

Website

intl.cloud.baidu.com/product/palo.html

Product Features

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Alternatives

Apache HBase Reviews

Apache HBase

The Apache Software Foundation

Alternatives

Apache Drill Reviews

Apache Drill

The Apache Software Foundation
Apache Sentry Reviews

Apache Sentry

Apache Software Foundation
Apache Kylin Reviews

Apache Kylin

Apache Software Foundation
Apache Hudi Reviews

Apache Hudi

Apache Corporation