Hive Technology offers their eponymous project management and process management application, providing integrations with many popularly used applications for productivity, cloud storage, and collaboration.
$12
per month per user
Kubernetes
Score 9.0 out of 10
N/A
Kubernetes is an open-source container cluster manager.
Hive is a powerful tool for data analysis and management that is well-suited for a wide range of scenarios. Here are some specific examples of scenarios where Hive might be particularly well-suited: 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.Simple queries on large datasets: Hive is optimized for simple queries on large datasets, making it a good choice for tasks such as data exploration and summary statistics. 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. On the other hand, here are some specific examples of scenarios where Hive might be less appropriate: Real-time queries: 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. While it is possible to use Hive for real-time queries, it may not be the most efficient choice for this type of workload. Complex queries: Hive is optimized for simple queries on large datasets, but may struggle with more complex queries or queries that require multiple joins or subqueries.Very large datasets: While Hive is designed to scale horizontally and can handle large amounts of data, it may not scale as well as some other tools for very large datasets or complex workloads.
K8s should be avoided - If your application works well without being converted into microservices-based architecture & fits correctly in a VM, needs less scaling, have a fixed traffic pattern then it is better to keep away from Kubernetes. Otherwise, the operational challenges & technical expertise will add a lot to the OPEX. Also, if you're the one who thinks that containers consume fewer resources as compared to VMs then this is not true. As soon as you convert your application to a microservice-based architecture, a lot of components will add up, shooting your resource consumption even higher than VMs so, please beware. Kubernetes is a good choice - When the application needs quick scaling, is already in microservice-based architecture, has no fixed traffic pattern, most of the employees already have desired skills.
Simplicity, it offers a clean environment without risking the outcome. An example of this are the timesheets that allow a fast way to keep track of progress
Interaction, the different options make it faster and easier to interact and collaborate in the development of a product. An example of this would be Hive Notes for meetings
The different visualisations it offers allow to explore the best ways to affront your projects. I really like the Gantt mappings view to understand who can be contacted at each point
Local development, Kubernetes does tend to be a bit complicated and unnecessary in environments where all development is done locally.
The need for add-ons, Helm is almost required when running Kubernetes. This brings a whole new tool to manage and learn before a developer can really start to use Kubernetes effectively.
Finicy configmap schemes. Kubernetes configmaps often have environment breaking hangups. The fail safes surrounding configmaps are sadly lacking.
It is an eminently usable platform. However, its popularity is overshadowed by its complexity. To properly leverage the capabilities and possibilities of Kubernetes as a platform, you need to have excellent understanding of your use case, even better understanding of whether you even need Kubernetes, and if yes - be ready to invest in good engineering support for the platform itself
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.
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 can easily track it.
Most of the required features for any orchestration tool or framework, which is provided by Kubernetes. After understanding all modules and features of the K8S, it is the best fit for us as compared with others out there.
