Hive Technology offers their eponymous project management and process management application, providing integrations with many popularly used applications for productivity, cloud storage, and collaboration.
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Nifty
Score 8.4 out of 10
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Nifty consolidates projects, work, and communications in one place. Nifty simplifies and automates the tracking of project milestones, communications with teammates and clients, collaborative document creation, and more in a centralized workspace! Nifty enables organizational oversight across projects and teammates with project & team workload overviews. With communications, project management, and workflow collaboration centralized in one place, teams can consolidate their workday as well…
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 …
More user-friendly. Able to quickly get users adopted and utilizing the platform versus Planview. More intuitive, especially for the user that is not familiar with project management software. This platform was built for everyday users.
Hive is a bit different than Jira and Monday, which I used mostly. Overall does a great job managing project and helps with team communication. Removes dependency of asking team members for updates by going to conference rooms. With Hive, the team updates the status, and we …
Hive did what these other tools do. It has Kanban boards, Gantt views, timeline views, reporting, task management, and file uploads. While it is not as feature rich at the lowest subscription level as some of these others, its interface is quite a bit less overwhelming than say …
Hive for me felt more complex and granular in comparison to other competitors which was a good thing. I enjoyed the layout of viewing projects, the way it integrated timesheets, resourcing, and budgets together, and worked really well to help track episodes and projects. For …
So far Hive is the total package for our needs. Offering request forms and proofing/approval out of the box without third party integrations has been a huge upgrade for us along with incredibly reasonable pricing. The support for onboarding has been fantastic and we haven't …
I would say that in comparison to Asana, Hive is a better interface an UI. I think Asana is more robust in terms of what it can do in conjunction with Confluence but I think Hive is a better entry-level model for new employees. Hive is much simpler and more straight forward and …
I like Hive better than Trello. Hive is definitely more user-friendly, but Trello had nice shortcuts that I miss in Hive. I would like to organize my board with just one click.
The one thing that makes this nifty stand out from its peers is its ability to support everything that one can think of while working/managing a project! It has got effective timeline management, charting capabilities, chat functionality, document storage, and the ability to …
We've tried several project management tools and most of them lacked the features we exactly needed. Jira was the last we tested and it was complicated to handle as projects grew bigger. Nifty is structured well and has major features that can handle big projects and does well …
There's no comparison. Nifty does what all of these do all in one place (with the exception of slack's community aspect with hashtagging - not sure if Nifty can do this, never tried)
Nifty even has the ability to import directly from many other platforms - I've personally …
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.
Nifty speeds up project lifecycles, aligns teams to work together to avoid missing deadlines and automates the process of reporting. Individual team members use Nifty to set their own project goals so that they can complete tasks on time. This app brings feedback together and offers teams dynamic collaboration to help them focus on the completion of the project.
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.
There's no comparison. Nifty does what all of these do all in one place (with the exception of Slack's community aspect with hashtagging - not sure if Nifty can do this, never tried) Nifty even has the ability to import directly from many other platforms - I've personally imported projects from Trello and Asana, saving tons of time in migration.
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