What users are saying about
81 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>Score 7.9 out of 100
Based on 81 reviews and ratings
24 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow noopener noreferrer'>trScore algorithm: Learn more.</a>Score 8.5 out of 100
Based on 24 reviews and ratings
Likelihood to Recommend
Apache Hive
Apache Hive shines for ad-hoc analysis and plugging into BI tools. Its SQL-like syntax allows for ease of use not for only for engineers but also for data analysts. Through our experience, there are probably more desirable tools to use if you are planning on integrating Hive into your processing pipeline.

Verified User
Engineer in Engineering
Computer Software Company, 51-200 employeesDatabricks Lakehouse Platform
Databricks has helped my teams write PySpark and Spark SQL jobs and test them out before formally integrating them in Spark jobs. Through Databricks we can create parquet and JSON output files. Datamodelers and scientists who are not very good with coding can get good insight into the data using the notebooks that can be developed by the engineers.

Verified User
Team Lead in Engineering
Financial Services Company, 10,001+ employeesFeature Rating Comparison
Platform Connectivity
Apache Hive
—
Databricks Lakehouse Platform
8.3
Connect to Multiple Data Sources
Apache Hive
—
Databricks Lakehouse Platform
9.0
Extend Existing Data Sources
Apache Hive
—
Databricks Lakehouse Platform
9.0
Automatic Data Format Detection
Apache Hive
—
Databricks Lakehouse Platform
7.0
Data Exploration
Apache Hive
—
Databricks Lakehouse Platform
6.0
Visualization
Apache Hive
—
Databricks Lakehouse Platform
6.0
Interactive Data Analysis
Apache Hive
—
Databricks Lakehouse Platform
6.0
Data Preparation
Apache Hive
—
Databricks Lakehouse Platform
8.0
Interactive Data Cleaning and Enrichment
Apache Hive
—
Databricks Lakehouse Platform
8.0
Data Transformations
Apache Hive
—
Databricks Lakehouse Platform
9.0
Data Encryption
Apache Hive
—
Databricks Lakehouse Platform
7.0
Built-in Processors
Apache Hive
—
Databricks Lakehouse Platform
8.0
Platform Data Modeling
Apache Hive
—
Databricks Lakehouse Platform
8.3
Multiple Model Development Languages and Tools
Apache Hive
—
Databricks Lakehouse Platform
9.0
Automated Machine Learning
Apache Hive
—
Databricks Lakehouse Platform
8.0
Single platform for multiple model development
Apache Hive
—
Databricks Lakehouse Platform
9.0
Self-Service Model Delivery
Apache Hive
—
Databricks Lakehouse Platform
7.0
Model Deployment
Apache Hive
—
Databricks Lakehouse Platform
7.5
Flexible Model Publishing Options
Apache Hive
—
Databricks Lakehouse Platform
7.0
Security, Governance, and Cost Controls
Apache Hive
—
Databricks Lakehouse Platform
8.0
Pros
Apache Hive
- Hive syntax is almost like SQL, so for someone already familiar with SQL it takes almost no effort to pick up Hive.
- To be able to run map reduce jobs using json parsing and generate dynamic partitions in parquet file format.
- Simplifies your experience with Hadoop especially for non-technical/coding partners.
Sr.Technical Manager/Delivery Manager
Nisum Technologies, Inc.Retail, 10,001+ employees
Databricks Lakehouse Platform
- Extremely Flexible in Data Scenarios
- Fantastic Performance
- DB is always updating the system so we can have latest features.

Verified User
Director in Information Technology
Financial Services Company, 201-500 employeesCons
Apache Hive
- Use Hive for analytical work loads. Write once and read many scenarios. Do not prefer updates and deletes.
- Behind scenes Hive creates map reduce jobs. Hive performance is slow compared to Apache Spark.
- Map reduce writes the intermediate outputs to dial whereas Spark operates in in-memory and uses DAG.

Verified User
Analyst in Engineering
Hospital & Health Care Company, 501-1000 employeesDatabricks Lakehouse Platform
- The navigation through which one would create a workspace is a bit confusing at first. It takes a couple minutes to figure out how to create a folder and upload files since it is not the same as traditional file systems such as box.com
- Also, when you create a table, if you forgot to copy the link where the table is stored, it is hard to relocate it. Most of the time I would have to delete the table and re-created.
Freelance Translator
ZOO Digital Group plcEntertainment, 501-1000 employees
Likelihood to Renew
Apache Hive
Apache Hive 10.0
Based on 1 answer
Since I do not know the second data warehouse solution that integrate with HDFS as well as Hive.
Senior Data Scientist
CARD.comFinancial Services, 11-50 employees
Databricks Lakehouse Platform
No score
No answers yet
No answers on this topic
Usability
Apache Hive
Apache Hive 8.5
Based on 9 answers
Thanks to its high usability Apache Hive enables users to craft extensive queries really efficiently and at the same time to how to hold response times very low. HiveQL simplicity makes it super easy to manage large datasets, what was almost an impossible task before introduction of Apache Hive data warehousing platform in our company.

Verified User
Team Lead in Information Technology
Internet Company, 10,001+ employeesDatabricks Lakehouse Platform
Databricks Lakehouse Platform 9.0
Based on 1 answer
This has been very useful in my organization for shared notebooks, integrated data pipeline automation and data sources integrations. Integration with AWS is seamless. Non tech users can easily learn how to use Databricks. You can have your company LDAP connect to it for login based access controls to some extent

Verified User
Team Lead in Engineering
Financial Services Company, 10,001+ employeesSupport Rating
Apache Hive
Apache Hive 7.1
Based on 8 answers
Hive also has a community platform of its own just like other Hadoop frameworks. Most of the queries/problems are resolved in the community itself. We can just post our problems or get in touch with a specific user and get the issue resolved. Otherwise there is always the product support team for any resolution.
Domain Consultant
InfosysInformation Technology & Services, 10,001+ employees
Databricks Lakehouse Platform
No score
No answers yet
No answers on this topic
Alternatives Considered
Apache Hive
Besides Hive, I have used Google BigQuery, which is costly but have very high computation speed.Amazon Redshift is the another product, I used in my recent organisation.Both Redshift and BigQuery are managed solution whereas Hive needs to be managed
Senior Manager - Engineering
Hike MessengerInternet, 51-200 employees
Databricks Lakehouse Platform
Easier to set up and get started. Less of a learning curve.

Verified User
Director in Engineering
Financial Services Company, 10,001+ employeesReturn on Investment
Apache Hive
- It exposes the distributed calculation world (Hadoop) to the users but doesn't require the user to have the in-depth understanding of boilerplate details, it reduces the time of learning and let the data analyst can focus their efforts on the core business.

Verified User
Strategist in Information Technology
Package/Freight Delivery Company, 10,001+ employeesDatabricks Lakehouse Platform
- Rapid growth of analytics within our company.
- Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value.
- Platform is easy to learn and Databricks provides excellent support and training.
- Platform does not require a large DevOPs investment

Verified User
Strategist in Engineering
Computer Hardware Company, 10,001+ employeesPricing Details
Apache Hive
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Apache Hive Editions & Modules
—
Additional Pricing Details
—Databricks Lakehouse Platform
General
Free Trial
—Free/Freemium Version
—Premium Consulting/Integration Services
—Entry-level set up fee?
No
Databricks Lakehouse Platform Editions & Modules
Edition
Standard | $0.071 |
---|---|
Premium | $0.101 |
Enterprise | $0.131 |
- Per DBU