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What is Datawisp?

Gaining coding proficiency shouldn't impede your access to vital information. Datawisp streamlines this journey by employing visual blocks instead of traditional coding: simply choose a data source, implement your transformations, and select your preferred output format. Our user-friendly visual query builder allows you to efficiently handle one or multiple datasets and present the results as either charts or tables. In addition to offering no-code query capabilities, Datawisp comes packed with numerous features intended to boost your team's data management skills and drive your business forward. Collaboration is effortless with Datawisp sheets, which are easily shareable, fostering real-time teamwork among users. Furthermore, our API grants you the versatility to retrieve analyses from external services and applications, facilitating the creation of in-game leaderboards, exporting wallet addresses for whitelists, and so much more, which ultimately broadens the potential of your projects. With Datawisp, you can focus on innovation and insights without the barriers that often accompany data handling.

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

Acceldata
Acryl Data
ActionIQ
Apache Avro
Apache Iceberg
Apache Impala
Apache Knox
DigDash
IBM API Connect
IBM Cloud Pak for Integration
IRI Voracity
Lyftrondata
Mage Dynamic Data Masking
Omniscope Evo
Predibase
StarRocks
Truedat
e6data
eQube®-DaaS
lakeFS

Integrations Supported

Acceldata
Acryl Data
ActionIQ
Apache Avro
Apache Iceberg
Apache Impala
Apache Knox
DigDash
IBM API Connect
IBM Cloud Pak for Integration
IRI Voracity
Lyftrondata
Mage Dynamic Data Masking
Omniscope Evo
Predibase
StarRocks
Truedat
e6data
eQube®-DaaS
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

Datawisp

Date Founded

2018

Company Location

United States

Company Website

www.datawisp.io

Company Facts

Organization Name

Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

hive.apache.org

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

ETL

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

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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