Hive vs. Stackby

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.

Incentivized

Based on my experience, I can provide specific scenarios where Stackby is well suited and others where it may be less appropriate: Project Management: Stackby is an excellent choice for project management scenarios. Its ability to create custom databases, track tasks, assign responsibilities, and collaborate in real-time makes it highly effective for managing and monitoring project progress. CRM and Sales: Stackby is well suited for managing customer relationships and sales processes. Its customizable database structure allows for organizing customer information, tracking leads, managing deals, and generating reports. The ability to integrate with other tools further enhances its usefulness in CRM and sales workflows. Content Planning: Stackby is a great fit for content planning scenarios. Users can create databases to manage editorial calendars, track content ideas, assign tasks to team members, and monitor content performance. Collaboration features facilitate seamless content collaboration and ensure timely publishing.

• 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.

Incentivized

• Ability to collaborate with team members on the same spreadsheet
• Ability to integrate multiple tools for centralized utilization (i.e. Facebook, Google Analytics, project management, etc.)
• Ability to send SMS and messages using integration with Twillio and Whatsapp
• All spreadsheets/databases securely saved in the cloud instead of on local hard drive(s)

• Organizing tasks by assignees could be better. It's a little cumbersome to check off each person you want. Can you group these?
• I don't really use any view besides task view. Is there something better I could be using?
• It would be nice if attachments showed up in a nicer format, maybe with a preview?

Incentivized

• Implement the same views available on desktop into the mobile app
• Internal automations (like Airtable)
• Ability to implement and display info as a dashboard (like Airtable)
• Polish up the formatting of formulas, inputting them causes user frustration due to the formula input cursor jumping around
• Better intelligence and ease of inputting data in bulk i.e have the fields automatically identify what data is being input and format appropriately (like Airtable does)

Its a easy tool, the best way to organize the workflow but has room for more improvements.

Stackby is overall pretty easy to use, especially if you're used to something like Airtable or SmartSuite. Some of the pages seem like near exact clones (though they put their own creative spin on things). I'd prefer a slighty fresher interface (like SmartSuite), but I'm willing to sacrifice that for the better price and great customer service.

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.

Incentivized

Extremely responsive, helpful, and friendly support (unlike many other SAAS teams out there).

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.

Incentivized

I have also tried Ora.Pm. Infinity has better graphical interface, but nowhere near as many features and the UI isn't as effective (i.e, moving around with keys). Grist has a much more technical interface and it comes from being more of a database/interactive spreadsheet vs Stackby. Grist has much more functionality in terms of formulas, but is much harder to learn to use and less other functionalities. Ora.PM is more of a test at a task management app, and doesn't compare - Stackby is much better.

• 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

Incentivized

• By its customisation, I have seen business intelligence that was not evident or available by using other software
• Has helped to organise all my data (work and personal) into interesting relationships that help with better decision making
• Has created extra curiosity in its flexibility and customisation to have all my datasets used and manipulated into meaningful ways