Hive Technology offers their eponymous project management and process management application, providing integrations with many popularly used applications for productivity, cloud storage, and collaboration.
$0
Pricing
Hive
Editions & Modules
Free
$0
Lite
$24
per month per user
Growth
$34
per month per user
Pro
$59
per month per user
Elite
Contact Sales
Offerings
Pricing Offerings
Hive
Free Trial
Yes
Free/Freemium Version
Yes
Premium Consulting/Integration Services
No
Entry-level Setup Fee
No setup fee
Additional Details
A discount is offered for annual pricing.
More Pricing Information
Community Pulse
Hive
Features
Hive
Project Management
Comparison of Project Management features of Product A and Product B
Hive
7.5
Ratings
2% below category average
Task Management
8.30 Ratings
Resource Management
7.30 Ratings
Gantt Charts
7.70 Ratings
Scheduling
7.90 Ratings
Workflow Automation
7.50 Ratings
Team Collaboration
8.00 Ratings
Support for Agile Methodology
8.30 Ratings
Support for Waterfall Methodology
7.60 Ratings
Document Management
7.10 Ratings
Email integration
7.30 Ratings
Mobile Access
7.00 Ratings
Timesheet Tracking
7.30 Ratings
Change request and Case Management
7.00 Ratings
Budget and Expense Management
6.60 Ratings
Professional Services Automation
Comparison of Professional Services Automation features of Product A and Product B
Hive is great for managing projects with your team. Assigning tasks is simple enough using Hive. It helps manage team goals for the projects. We are able to create reports (via the dashboard) for the progress and updates to provide to the team based on completed stages. Works great for bigger projects.
Data warehousing: Hive is often used as a data warehousing platform, allowing users to store and analyze large amounts of structured and semi-structured data. It is especially good at handling data that is too large to be stored and analyzed on a single machine, and supports a wide variety of data formats.
Batch processing: Hive is designed for batch processing of large datasets, making it well-suited for tasks such as data ETL (extract, transform, load), data cleansing, and data aggregation.
Data transformation: Hive allows users to perform data transformations and manipulations using custom scripts written in Java, Python, or other programming languages. This can be useful for tasks such as data cleansing, data aggregation, and data transformation.
Integration with other tools: Hive integrates with a wide variety of other tools and services in the Hadoop ecosystem, such as Pig, Spark, and HBase, allowing users to perform a wide range of data analysis and management tasks.
Our CSR is easily accessible and they have support built into the app itself. They also have a pretty robust support site. We also took advantage of the free trial and learned so much by putting Hive through the paces and figuring out the best way to mold it to our needs.
One key difference between Hive and Spark is the way they process data. Hive is a batch-oriented system, which means that it is designed to process large amounts of data in a batch mode rather than in real-time. In contrast, Spark is a real-time processing platform that is designed to handle streaming data and support interactive queries. Another difference is the way they execute queries. Hive uses a SQL-like query language called HiveQL, while Spark supports a wide range of languages and APIs, including SQL, Python, Scala, and R. But we chose Hive due to its simple queries on large datasets and for data warehousing tasks.
I've gotten to know my colleagues better, knowing their roles makes it faster to contact them to complete tasks and that speed makes us optimize and earn better results
The jobs speed made us focus on optimization and customization for the client, and that in a better treatment by the client and better revenue
We can understand which tasks takes more time and to stimate better what we can ask for
