Trifacta is a "data wrangling" (or data preparation) platform particularly of use with Hadoop, developed by the company Trifacta headquartered in San Francisco, California. Alteryx announced their acquisition of Trifacta in January of 2022.
$100
per month per user
Hive
Score 8.4 out of 10
N/A
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
Pricing
Alteryx Designer Cloud
Hive
Editions & Modules
Starter
$100
per month per user
Professional
$500
per month per user
Enterprise
Custom
No answers on this topic
Offerings
Pricing Offerings
Alteryx Designer Cloud
Hive
Free Trial
Yes
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Starter & Professional plans include a charge of + $0.60 / vCPU hour. 20% discount for annual pricing.
For doing ETL and data transformations where your data is already in a cloud environment Alteryx Designer Cloud is ideal. It allows for the continued democratisation of data and analytics to permeate more extensively throughout a business, particularly those that are already in the cloud or have cloud services in place and are comfortable with procurement and consumption of these systems over and above desktop software. The ETL processing for data validation and wrangling uses machine learning to enable highly efficient data manipulation which saves lots of time and this is a distinct advantage over the desktop software. The expansion and integration of other Alteryx cloud services such as ML, Metrics Store and App builder will only strengthen this position
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.
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
I feel like the usability works for every level of computer user. There are very simple tools that can accomplish a huge amount of time savings, and there are very complex tools that can give you even more. We mainly use just the simple tools in our company and have gained an incredible amount of time savings
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.
Our IT group presented Trifacta to me. They picked it out and among the crowd for me. This was way beyond ETL tools, SQL, or any programming language. It's just much faster and because it's sitting on Hadoop you bypass some of the slowdowns typically faced with RDBMS.
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.
