Apache Hive is an open-source, distributed, and fault-tolerant data warehouse system that assists with analytics at a massive scale.
Are you curious about how Hive works or how it can benefit your business?
If so, this article is for you. It answers some of your most pressing questions about Hive, including what it is, its benefits and drawbacks, and how it can be used for business intelligence.
What Is Hive?
Apache Hive is built on Apache Hadoop — a framework for distributed storage and Big Data processing — and allows for advanced work on the Hadoop Distributed File System (HDFS) and MapReduce.
It supports storage on S3, ADS, and more through HDFS. With Hive, SQL developers can also write Hive Query Langauge statements, which are similar to standard SQL statements.
The Hive system offers several unique features that make it a popular option among professionals looking for better data storage options. The following are some of its most significant features:
Hive-Server 2 (HS2)
HS2 allows for multi-client use and authentication. It also offers superior support for open API clients, including ODBC and JDBC.
Hive Metastore Server (HMS)
HMS is a central storage location containing metadata for Hive tables and partitions in a relational database. It also provides clients with access to this information through the metastore service API.
The Hive Metastore Server is a primary data lake tool that utilizes open-source software like Apache Spark and Presto. Numerous solutions, both open-source and otherwise, have been developed around the Hive Metastore, and more will indeed be added in the future.
Hive Data Compaction
Hive supports query-based and MR-based data compactions straight out of the box.
Hive supports bootstrap and incremental replication for enhanced data backup and recovery.
Security and Observability
Apache Hive supports Kerberos — a trusted protocol that authenticates service requests. It also integrates with other security and observability tools like Apache Ranger and Apache Atlas.
Since it was released in 2010, it has been a popular solution for data warehousing. If you decide to use it, you and your team will experience the following benefits:
One of the greatest perks of this BI tool is its affordability. If your organization wants to maximize profits, it provides significant returns on investment and is much less expensive than other big data analysis tools.
It’s important to note that Hive does use specific advanced software development tools that not all organizations have access to. You may need to spend additional money upfront to get these technologies.
For starters, this tool uses batch processing, which speeds up the data analysis process by dividing data into bits and analyzing them separately. This process is more advanced than what many other tools use. It also allows Hive to handle massive amounts of data simultaneously.
It is also known for its reliability and fault tolerance. It outshines many other Big Data analysis systems, primarily because it works with Hadoop’s Distributed File System, which replicates data whenever it analyzes, preventing data loss in case of a machine malfunction.
In addition, it works well for complex coding projects because it allows users to divide work and assign equal work to all developers. It also uses methods like filtering to ensure developers are carrying out tasks assigned to them specifically.
Superior Customer Support
Hive is accompanied by a team of members who are ready and willing to respond to questions and concerns. The support team also ensures that it is consistently modified and improved, allowing users to have the best experience possible.
Although it offers many advantages over other solutions, Hive also comes with some potential downsides. The cons discussed below are the most important ones to consider:
Not User-Friendly for Beginners
Those who are new to the world of Big Data may struggle to use Hive at first. They’ll have to take extra time to learn how the application works, especially when it comes to functions like configuration and personalization.
Limited Mobile Functionality
Also, it does not work as well on a mobile device as it does on a desktop. However, this particular con isn’t an obstacle for too many people since most BI professionals and their teams aren’t trying to do complex data analysis from their phones.
Task Creation Limitations
Some projects can require users to create dependent tasks, which can be problematic on the platform.
Although it comes with automated workflow options, it cannot create dependent tasks. Instead, users must manually create recurring tasks.
How Can Hive Be Used for Business Intelligence?
Business intelligence professionals can use Apache Hive for highly efficient data extraction, analysis, and processing.
One of the most significant benefits of this tool for business intelligence is the fact that it works with several data types divided into five primary categories:
- Numeric: Integer-based data types (‘TINYINT,’ ‘SMALLINT,’ ‘INT,’ ‘BIGINT’)
- Date/Time: Data types that allow users to input times and dates (‘TIMESTAMP,’ ‘DATE,’ ‘INTERVAL’)
- String: Data types that permit written text to be implemented as data (‘STRING,’ ‘VARCHAR,’ and ‘CHAR’)
- Complex: Advanced data types that record elaborate data (‘STRUCT,’ ‘MAP,’ ‘ARRAY,’ ‘UNION’)
- Misc. Types: Data types that don’t fit into any of the previous categories ( ‘BOOLEAN,’ ‘BINARY’)
BI professionals will also appreciate the distinctions between Apache Hive and a traditional Relational Database Management System (RDBMS).
Hive does use an RDBMS to ensure all data is safely, reliably, and accurately stored and processed. It utilizes integrated features like role-based security and encryption to provide only certain people access to the extracted information.
There are also some critical differences between Hive and a traditional RDBMS, including the following:
- RDBMS functions work on “read” and “write” many times; Hive works on “write” once and “read” many times.
- Hive follows the schema-on-read rule (meaning there’s no data checking, parsing, validation, only file copying, and moving); In traditional databases, a schema gets applied to a table and enforced on a “write” rule.
Hive also complies with the same safety, security, and use restrictions as Hadoop and MapReduce (since it’s built on top of Hadoop). Other RDBMS solutions may not.
Yurbi and Hive: How We Can Help
So similar to its sisters Apache Spark and Hadoop, there is no native integration available yet to connect Yurbi directly to Apache Hive. The good news is, we can still make things work by using third-party ODBC drivers.
Yurbi doesn't have the capability to communicate with Hive directly via their CQL. However, it does offer support for 3rd party ODBC drivers, which enable communication with it in a way similar to that of a relational database. CDATA and Progress are some of the best examples you can use to connect Yurbi and Apache Hive to make things work.
Also, with Yurbi, users can easily create reports and dashboards that combine data from there with other data sources (this links to data visualization). Additionally, Yurbi enables users to query and extract data without requiring direct access to Hive or advanced technical skills in writing queries.
Apart from that, there are other things that Yurbi can also do, such as data visualization, embedded analytics, and other things related to business intelligence. It has a wide range of features you can use to streamline your business operations.
Consider Yurbi your jack-of-all-trades in terms of business intelligence and modern embedded analytics.
You might wonder that with all these superb offerings, Yurbi might come with a hefty price tag. Well, here’s another thing to sweeten the deal: all of these are for lower rates than the competition.
Yurni’s more affordable pricing points are geared towards small and medium-sized business owners who wish to innovate and optimize their BI toolboxes with a great BI tool like Yurbi.
So what are you waiting for? Avail of our free live demo sessions or sit down and have a meeting with us to further discuss your needs and how we can meet those with Yurbi.