Hire a Hive Engineer

Apache Hive is a data warehouse software built on top of Hadoop. Its main goal is to provide an interface for querying and managing large datasets in a cluster, which is similar to a traditional database management system. By hiring a Hive engineer, your business can leverage Apache Hive to create tables, insert data, query the tables, perform aggregations, and more. Apache Hive provides data warehouse functionality that makes it easier for developers with SQL skills to query large datasets stored in Hadoop clusters. As the trend of big data continues to grow, the demand for Hive developers is also beginning to rise.
Hive Engineer

Responsibilities of a Hive Engineer

A Hive engineer’s main duties include development and coding. This job requires similar skills to that of a web developer. Some of the most common responsibilities of a Hive developer include:

  • Providing Hive design and implementation
  • Developing guidelines and principles suggestions
  • Ensuring data security
  • Querying at a rapid pace
  • Obtaining information from a variety of sources
  • Creating versatile and high-performing online performance monitoring services
  • Administering and deploying HBase
  • Analyzing massive quantities of data and discovering new insights
  • Transforming complex functional and technical requirements into complete designs

FAQs About Hiring Hive Engineers

What is Apache Hive used for?

Hive is a data warehouse tool that allows you to handle structured data. It is built on top of Hadoop to summarize large amounts of data and simplify querying and analyzing the data.

Initially, Facebook created Hive, but it was subsequently adopted by the Apache Software Foundation, which continued to develop it as an open-source project under Apache Hive. A variety of businesses use it. Amazon, for example, makes use of Apache Hive in their Amazon Elastic MapReduce service.

Hive is best used for operations such as:

  • Data encapsulation
  • Specific queries
  • Analysis of huge datasets
What is the difference between Hive and Hadoop?

Hadoop is a framework designed to handle large data sets. Hadoop stores and processes massive data sets on servers. Hadoop also uses a distributed file system to store data and employs a Map-Reduce programming paradigm to handle it.

Hive is a Hadoop application that offers a SQL-like interface for processing and querying data. Hive has the same structure as a Relational Database Management system and uses nearly the same commands, however, it relies on HQL (Hive query language) to query. In addition, Hive can store data in external tables and supports multiple file formats, including ORC, Avro, Sequence File, and Text File.

How can High5 help me hire a Hive engineer?

It may be challenging to get started when hiring a Hive developer for your company. First and foremost, it’s important to think about what skills you will need and how long it will take. Before recommending a developer, High5 experts assess an organization's goals. Then, based on the skills required for the job, we will match qualifying Hive engineers to your business or project, ensuring that you are matched with the best candidate for the job every time.

Guide to Hiring a Hive Engineer

Apache Hive is an SQL-like query language for querying data stored in Hadoop. Hive provides a data warehouse, business intelligence, and analytic application that runs on top of Hadoop. It allows users to execute queries against large datasets in a warehouse fashion, similar to how they would run a traditional relational database system. Apache Hive is regarded as a quick and dependable tool to store and handle large amounts of data.

If your company were to hire a Hive engineer, it can experience all of these benefits and more.

What is Apache Hive?

Apache Hive is an open-source data warehouse system developed by Facebook. It facilitates querying and managing large datasets residing in distributed storage, like Apache Hadoop Distributed File System (HDFS).

Hive can be used with various file formats, notably including Apache Parquet, ORC, JSON, and RCFile. While the original version of Hive ran exclusively on top of HDFS, it now supports other file systems, such as GPFS, MapR-FS, and Amazon S3. With this new functionality, you can simplify things even further if you were to hire a Hive engineer that can analyze files from other platforms, such as Microsoft Azure or Google Cloud Platform while benefiting from the familiar SQL interface.

How Hive Engineers Use Hive

Hive has two interfaces: a declarative query language called HiveQL and a set of Java libraries known as The Hive Java Application Programming Interface (API). HiveQL provides operations for common data manipulations, such as filtering, sorting, grouping, joining, projecting, and analyzing. The Hive Java API is also used to manage the runtime environment for queries.

Facebook created the Apache Hive project to provide interactive querying of datasets stored in the Hadoop Distributed File System (HDFS) offered by Apache. The project was initially named “Pig SQL” because its syntax was similar to that of the programming language SQL, but as it evolved, it became a more general-purpose system with richer functionality, so its name was changed.

While Apache Hive typically requires an advanced level of technical knowledge to understand, we have gathered three main takeaways that Apache Hive has enabled users to do:

  • The ability to summarize evaluation data contained in both basic and derived data in order to finally construct generalized evaluation data
  • The ability to request the database for information
  • The ability to perform ad-hoc analysis on large amounts of data rapidly and efficiently
Here are some common business use cases of Hive:
  • User segmentation and preference analysis using clickstream data
  • Tracking data such as ad usage
  • Internal and external research reporting and analytics
  • Web, mobile, and cloud application internal log analysis
  • Exact pattern data mining
  • Data parsing and learning for predictions
  • Machine learning to cut operating costs

Hive is Popular With Businesses and Developers

Apache Hive technology is one of the most powerful tools to help organizations make sense of their data. Hadoop and Hive are used by many companies worldwide, and they can be found in a variety of industries, such as finance, healthcare, and retail.

The query type of Hive auto-translates to a SQL-like query; developers are familiar with this type of query. It also satisfies customers searching for a database solution that resembles SQL. Because Apache Hive can perform operations like ad-hoc data analysis so fast, businesses seeking more efficient record keeping find Apache Hive helpful. Its combination of massive data storage and analysis makes it an industry leader.

Among its many excellent features, Hive can manage many data types in a Hadoop context. Hadoop was designed to hold vast volumes of data in various forms, sizes, and formats. As a result, it’s very flexible in what type of data you can analyze. You can upload anything from CSV files to JSON objects through web APIs or S3 buckets. This makes it simple for a Hive developer to build a fully working database for various business needs.

Why Should You Hire a Hive Engineer?

There are many benefits of using Hive for your big data needs, but you should hire a Hive engineer to ensure you are reaping the benefits of Hive to the fullest. Here are just a few benefits of using Hive alongside a specialized Hive developer:

Querying Is Made Simple

Querying data is simple using Hive’s SQL-like language. Hive developers will be most familiar with the language.

Quick Schema Detection

Apache Hive reads the schema without validating the table type or schema definition, allowing for faster initial data entry. A typical database requires data to be validated every time it is added.

Smooth Scaling

Apache Hive stores 100s of petabytes of data on HDFS, giving it a significantly more scalable alternative than a typical database. Apache Hive’s cloud-based Hadoop solution allows customers to scale virtual machines to meet changing workloads quickly.

Exceptional Security

Apache Hive is part of Hadoop security, which leverages Kerberos for client-server mutual authentication. HDFS controls permissions by user, group, and others for freshly generated files in Apache Hive. An Apache Hive developer will be most familiar with Hive’s security features.

User and Cloud-Friendly

Insert-only tables typically have little-to-no overhead. When you hire a Hive engineer, he or she can enjoy a cloud-friendly approach, since no renaming is necessary. In addition, Hive contains huge databases that can support up to 100,000 queries per hour.

Final Words on Hiring a Hive Engineer

Any big data activity that involves summarization, analysis, and ad-hoc querying of enormous datasets spread across a cluster should consider using Apache Hive. With big data integrated and readily available, your company can learn about prospective consumers’ demands. Many companies such as Netflix and Amazon are already taking advantage of Hive’s many benefits.

To truly gain the full value of Apache Hive, you must hire an Apache developer who is experienced and knowledgeable. High5 can help. Before we recommend any candidates to you, we first get a deep understanding of your goals and objectives. Then, we can connect you with the best developers for your project or task.

Start your hiring process with High5 now and add a skilled Hive engineer to your team.

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