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
MySQL
Score 8.0 out of 10
N/A
MySQL is a popular open-source relational and embedded database, now owned by Oracle.
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Pricing
Hive
MySQL
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
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Offerings
Pricing Offerings
Hive
MySQL
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
A discount is offered for annual pricing.
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More Pricing Information
Community Pulse
Hive
MySQL
Features
Hive
MySQL
Project Management
Comparison of Project Management features of Product A and Product B
Hive
7.5
Ratings
2% below category average
MySQL
-
Ratings
Task Management
8.30 Ratings
00 Ratings
Resource Management
7.30 Ratings
00 Ratings
Gantt Charts
7.70 Ratings
00 Ratings
Scheduling
7.90 Ratings
00 Ratings
Workflow Automation
7.50 Ratings
00 Ratings
Team Collaboration
8.00 Ratings
00 Ratings
Support for Agile Methodology
8.30 Ratings
00 Ratings
Support for Waterfall Methodology
7.60 Ratings
00 Ratings
Document Management
7.10 Ratings
00 Ratings
Email integration
7.30 Ratings
00 Ratings
Mobile Access
7.00 Ratings
00 Ratings
Timesheet Tracking
7.30 Ratings
00 Ratings
Change request and Case Management
7.00 Ratings
00 Ratings
Budget and Expense Management
6.60 Ratings
00 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.
From my own perspective and the tasks that I perform on a daily basis, MySQL is perfect. It has a reasonable footprint, is fast enough and offers the security and flexibility I need. Everyone has their preferred applications and, no doubt, for larger data warehouses or more intensive applications, MySQL may have its limits, but for the area that I operate in, it's a great match.
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.
Security: is embedded at each level in MySQL. Authentication mechanisms are in place for configuring user access and even service account access to applications. MySQL is secure enough under the hood to store your sensitive information. Also, additional plugins are available that sit on top of MySQL for even tighter security.
Widely adopted: MySQL is used across the industry and is trusted the most. Therefore, if you face any problems, simply Google it and you shall land in plenty of forums. This is a great relief as when you are in a need of help, you can find it right in your browser.
Lightweight application: MySQL is not a heavy application. However, the data you store in the database can get heavy with time, but as in the configuration and MySql application files, those are not very heavy and can easily be installed on legacy systems as well.
Although you can add the data you require as more and more data is added, the fixity of it becomes more critical.
As the demand, size, and use of the system increase, you may also need to change or acquire more equipment on your servers, although this is an internal inconvenience for the company.
For teaching Databases and SQL, I would definitely continue to use MySQL. It provides a good, solid foundation to learn about databases. Also to learn about the SQL language and how it works with the creation, insertion, deletion, updating, and manipulation of data, tables, and databases. This SQL language is a foundation and can be used to learn many other database related concepts.
I give MySQL a 9/10 overall because I really like it but I feel like there are a lot of tech people who would hate it if I gave it a 10/10. I've never had any problems with it or reached any of its limitations but I know a few people who have so I can't give it a 10/10 based on those complaints.
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.
The support staff is friendly, knowledgeable, and efficient. I only had to get part way through my explanations before they had a solution. They will walk you through a fix or actually connect in and fix the problem for you--or would if you can allow it. I've done it both ways with them. They are always forthcoming with 'how to do this if it happens again' information. I love working with MySQL support.
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.
Each of the products has its own merits and demerits. however since MySQL is a very good documentation and global community its easy to learn and apply in different stages for analytics work. compare to other data bases its simple for setup and work on it. MySQL is cost effective and low risk choice for start up organization makes it more suitable for small to medium enterprises.
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