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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
Dynamic and engaging visualizations enable the discovery of trends within user and business processes, offering comprehensive insight into the foundational computations. A concise collection of sequential operations delivers extensive functionality and meticulous control, all achievable in fewer than ten lines of code. An adaptive query engine allows users to effortlessly balance the trade-offs between query accuracy, processing speed, and costs to suit their specific requirements. Currently, Motif employs a specialized domain-specific language known as Sequence Operations Language (SOL), which we find to be more intuitive than SQL while providing greater capabilities than a simple drag-and-drop interface. Additionally, we have developed a bespoke engine designed to enhance the efficiency of sequence queries, while strategically sacrificing unnecessary precision that does not contribute to decision-making, in favor of improving query performance. This approach not only streamlines the user experience but also maximizes the effectiveness of data analysis.
API Access
Has API
API Access
Has API
Integrations
Acryl Data
Algonomy
Apache Kylin
Aqua Data Studio
ClicData
Data Virtuality
DataClarity Unlimited Analytics
Datalogz
E-MapReduce
IBM Cloud Mass Data Migration
Integrations
Acryl Data
Algonomy
Apache Kylin
Aqua Data Studio
ClicData
Data Virtuality
DataClarity Unlimited Analytics
Datalogz
E-MapReduce
IBM Cloud Mass Data Migration
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Apache Software Foundation
Founded
1999
Country
United States
Website
hive.apache.org
Vendor Details
Company Name
Motif Analytics
Founded
2022
Country
United States
Website
www.motifanalytics.com
Product Features
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Product Features
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery
Web Analytics
Campaign Management
Conversion Tracking
Form Analytics
Goal Tracking
Keyword Tracking
Multiple Site Management
Pageview Tracking
Referral Source Tracking
Site Search Tracking
Time on Site Tracking
User Interaction Tracking