Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Google BigQuery
Score 8.6 out of 10
N/A
Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
$0
per month
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
Google BigQueryHive
Editions & Modules
Standard edition
$0.04 / slot hour
Enterprise edition
$0.06 / slot hour
Enterprise Plus edition
$0.10 / slot hour
No answers on this topic
Offerings
Pricing Offerings
Google BigQueryHive
Free Trial
YesYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Google BigQueryHive
Considered Both Products
Google BigQuery

No answer on this topic

Hive
Chose Hive
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 …
Top Pros
Top Cons
Features
Google BigQueryHive
Database-as-a-Service
Comparison of Database-as-a-Service features of Product A and Product B
Google BigQuery
8.5
51 Ratings
3% below category average
Hive
-
Ratings
Automatic software patching8.117 Ratings00 Ratings
Database scalability8.851 Ratings00 Ratings
Automated backups8.524 Ratings00 Ratings
Database security provisions8.844 Ratings00 Ratings
Monitoring and metrics8.546 Ratings00 Ratings
Automatic host deployment8.113 Ratings00 Ratings
Project Management
Comparison of Project Management features of Product A and Product B
Google BigQuery
-
Ratings
Hive
7.7
15 Ratings
2% above category average
Task Management00 Ratings8.515 Ratings
Resource Management00 Ratings7.515 Ratings
Gantt Charts00 Ratings8.014 Ratings
Scheduling00 Ratings7.914 Ratings
Workflow Automation00 Ratings7.614 Ratings
Team Collaboration00 Ratings8.115 Ratings
Support for Agile Methodology00 Ratings8.312 Ratings
Support for Waterfall Methodology00 Ratings7.711 Ratings
Document Management00 Ratings7.313 Ratings
Email integration00 Ratings7.513 Ratings
Mobile Access00 Ratings6.911 Ratings
Timesheet Tracking00 Ratings7.79 Ratings
Change request and Case Management00 Ratings7.411 Ratings
Budget and Expense Management00 Ratings6.89 Ratings
Professional Services Automation
Comparison of Professional Services Automation features of Product A and Product B
Google BigQuery
-
Ratings
Hive
7.3
12 Ratings
2% below category average
Quotes/estimates00 Ratings7.010 Ratings
Invoicing00 Ratings7.47 Ratings
Project & financial reporting00 Ratings8.010 Ratings
Integration with accounting software00 Ratings7.09 Ratings
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Google BigQueryHive
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User Ratings
Google BigQueryHive
Likelihood to Recommend
8.6
(51 ratings)
8.4
(15 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
Usability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
10.0
(9 ratings)
9.4
(2 ratings)
Contract Terms and Pricing Model
10.0
(1 ratings)
-
(0 ratings)
Professional Services
8.2
(2 ratings)
-
(0 ratings)
User Testimonials
Google BigQueryHive
Likelihood to Recommend
Google
For organizations looking to avoid the overhead of managing infrastructure, BigQuery's server-less architecture allows teams to focus on analyzing data without worrying about server maintenance or capacity planning. Small projects or startups with limited data analysis needs and tight budgets might find other solutions more cost-effective. Also, it is not suitable for OLTP systems.
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Hive Technology
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.
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Pros
Google
  • Its serverless architecture and underlying Dremel technology are incredibly fast even on complex datasets. I can get answers to my questions almost instantly, without waiting hours for traditional data warehouses to churn through the data.
  • Previously, our data was scattered across various databases and spreadsheets and getting a holistic view was pretty difficult. Google BigQuery acts as a central repository and consolidates everything in one place to join data sets and find hidden patterns.
  • Running reports on our old systems used to take forever. Google BigQuery's crazy fast query speed lets us get insights from massive datasets in seconds.
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Hive Technology
  • 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
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Cons
Google
  • Can't use it out of Google's cloud platform which is a minus point if you want a local setup.
  • Can be a little expensive to manage.
  • A little difficult to manage someone with less technical expertise as it requires you to have SQL knowledge of joins, CTEs etc.
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Hive Technology
  • 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?
Read full review
Likelihood to Renew
Google
We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.
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Hive Technology
No answers on this topic
Usability
Google
web UI is easy and convenient. Many RDBMS clients such as aqua data studio, Dbeaver data grid, and others connect. Range of well-documented APIs available. The range of features keeps expanding, increasing similar features to traditional RDBMS such as Oracle and DB2
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Hive Technology
No answers on this topic
Support Rating
Google
BigQuery can be difficult to support because it is so solid as a product. Many of the issues you will see are related to your own data sets, however you may see issues importing data and managing jobs. If this occurs, it can be a challenge to get to speak to the correct person who can help you.
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Hive Technology
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.
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Alternatives Considered
Google
Google's Firebase isn't a competitor but we had to use Google's BigQuery because Google's Firebase's database is limited compared to Google's BigQuery. Linking your Firebase project to BigQuery lets you access your raw, unsampled event data along with all of your parameters and user properties. Highly recommend connecting the two if you have a mobile app.
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Hive Technology
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.
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Contract Terms and Pricing Model
Google
None so far. Very satisfied with the transparency on contract terms and pricing model.
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Hive Technology
No answers on this topic
Professional Services
Google
Google Support has kindly provide individual support and consultants to assist with the integration work. In the circumstance where the consultants are not present to support with the work, Google Support Helpline will always be available to answer to the queries without having to wait for more than 3 days.
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Hive Technology
No answers on this topic
Return on Investment
Google
  • Google BigQuery has had enormous impact in terms of ROI to our business, as it has allowed us to ease our dependence on our physical servers, which we pay for monthly from another hosting service. We have been able to run multiple enterprise scale data processing applications with almost no investment
  • Since our business is highly client focused, Google Cloud Platform, and BigQuery specifically, has allowed us to get very granular in how our usage should be attributed to different projects, clients, and teams.
  • Plain and simple, I believe the meager investments that we have made in Google BigQuery have paid themselves back hundreds of times over.
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Hive Technology
  • Workflow Management will help you better move your projects along which saves time and money.
  • Time tracking will allow you to better manage the hours and keep your contractors accountable.
  • Overall visibility of projects allow you to keep your margins down and combat "bleeding" and hidden costs or surprises.
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ScreenShots

Hive Screenshots

Screenshot of HIver Technology