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Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
1,937
aziende
Abbiamo dati su 1,937 aziende che usano Apache Hive. La nostra lista di clienti Apache Hive è disponibile per il download ed è arricchita con specifiche vitali dell'azienda, incluse classificazione industriale, dimensioni organizzative, posizione geografica, round di finanziamenti e cifre di ricavi, tra gli altri.
Azienda | Paese | Settore | Dipendenti | Entrate |
---|---|---|---|---|
ScanmarQED | Paesi Bassi | Financial Services | 50 | $4.7M |
EY | Regno Unito | Professional Services | 357K | $45B |
![]() Cloudera | Stati Uniti | Software Development | 3.1K | $905M |
IBM | Stati Uniti | It Services And It Consulting | 309K | $61B |
ENSIGN INFOSECURITY (CYBERSECURITY) PTE. LTD. | Singapore | Professional Services | 580 | |
Dice | Stati Uniti | Software Development | 736 | $12M |
Royal Bank of Canada | Canada | Banking | 84K | $36B |
![]() Deutsche Bank | Germania | Financial Services | 85K | $29B |
Infogain | Stati Uniti | It Services And It Consulting | 5.7K | $520M |
JPMorgan Chase Bank, N.A. | Stati Uniti | Financial Services | 76K | $135M |
General Motors | Stati Uniti | Motor Vehicle Manufacturing | 167K | $161B |
Citi | Stati Uniti | Financial Services | 200K | $75B |
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Apache Hive è utilizzata in 50 paesi
Domande frequenti
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Apache Hive is an open-source data warehouse infrastructure built on top of Apache Hadoop for providing data summarization, query, and analysis. It facilitates querying and managing large datasets residing in distributed storage. Designed for scalability, Hive enables users to work with petabytes of data using SQL-like queries through its HiveQL language, which translates queries into Hadoop MapReduce jobs. Apache Hive aims to make querying of Big Data accessible to those familiar with SQL.
Apache Hive falls under the category of Big Data Tools, catering to the growing need for processing and analyzing massive volumes of data. It is particularly useful for organizations dealing with structured and semi-structured data sets that require relational database-style operations. By utilizing a familiar SQL syntax, users can leverage Apache Hive to extract insights from large datasets without needing to learn complex programming languages.
Apache Hive was founded in 2008 by Facebook as an open-source project to address the need for querying and analyzing large datasets generated by their social media platform. The motivation behind Hive's development was to provide a user-friendly interface for data processing on Hadoop, enabling data analysts and engineers to perform analytics at scale. Since then, the project has gained significant traction in the Big Data ecosystem.
As of the latest data available, Apache Hive holds a notable market share within the Big Data Tools category. With the increasing adoption of Big Data technologies across industries, it is expected that Apache Hive's market share will continue to grow in the future. The scalability, flexibility, and SQL compatibility of Hive position it as a valuable tool for organizations looking to harness the power of Big Data for decision-making and analytics.
Apache Hive is a powerful tool widely used by companies in the realm of Big Data to efficiently manage and analyze large datasets stored in Hadoop distributed file system. The structured query language (SQL) interface provided by Hive allows users to query, summarize, and analyze data seamlessly, making it a popular choice for organizations dealing with massive amounts of data.
Apache Hive optimizes query execution by translating SQL queries into MapReduce jobs, thereby improving performance over traditional database systems. This approach enhances processing speed and allows for faster data analysis compared to other similar technologies.
With Apache Hive, companies can easily scale their data processing capabilities by leveraging the distributed computing power of Hadoop. As data volumes grow, Hive can seamlessly handle the increased workload without compromising performance, offering superior scalability compared to standalone database solutions.
Apache Hive provides robust data warehousing functionalities, allowing organizations to create structured tables, manage schemas, and perform complex data analysis tasks. Its support for partitioning and bucketing enables efficient data organization, making it an ideal choice for building data warehouses when compared to traditional SQL databases.
Apache Hive seamlessly integrates with various ecosystem tools within the Hadoop ecosystem, such as Apache Spark and Apache HBase. This interoperability enables companies to create comprehensive data pipelines and perform diverse data processing tasks, offering a more holistic approach compared to standalone data processing tools.
Apache Hive stands out as a valuable asset for companies looking to streamline their Big Data processing workflows, thanks to its robust features, scalability, and seamless integration capabilities.
Apache Hive is a powerful tool used by several prominent companies to manage and analyze large volumes of data efficiently. Below are some real-world case studies showcasing how companies have leveraged Apache Hive for their data processing needs in the realm of Big Data Tools.
1. Facebook Facebook, a social media giant, utilizes Apache Hive as part of its data infrastructure to process and analyze vast amounts of user-generated data. The company started using Apache Hive several years ago to help optimize queries for complex data analytics tasks, enabling faster insights extraction and informed decision-making.
2. Netflix Netflix, a leading streaming service provider, relies on Apache Hive to handle its massive datasets for content recommendations, viewer behavior analysis, and backend operations. By implementing Apache Hive, Netflix has streamlined data processing workflows, improved query performance, and enhanced data accessibility across teams since the inception of its usage.
3. LinkedIn LinkedIn, the professional networking platform, employs Apache Hive for a wide range of data processing tasks, such as user behavior analysis, content personalization, and business intelligence reporting. By adopting Apache Hive into its data ecosystem, LinkedIn has seen notable improvements in query efficiency, data processing speed, and overall scalability ever since incorporating the technology.
These case studies offer a glimpse into how industry leaders like Facebook, Netflix, and LinkedIn have successfully integrated Apache Hive into their operations to harness the power of Big Data Tools for transformative insights and streamlined data management.
Puoi accedere a un elenco aggiornato di aziende che utilizzano Apache Hive visitando TheirStack.com. La nostra piattaforma fornisce un database completo di aziende che utilizzano varie tecnologie e strumenti interni.
Fino ad ora, abbiamo dati su 1,937 aziende che utilizzano Apache Hive.
Apache Hive è utilizzato da una vasta gamma di organizzazioni in vari settori, inclusi "Financial Services", "Professional Services", "Software Development", "It Services And It Consulting", "Professional Services", "Software Development", "Banking", "Financial Services", "It Services And It Consulting", "Financial Services". Per un elenco completo di tutti i settori che utilizzano Apache Hive, si prega di visitare TheirStack.com.
Alcune delle aziende che utilizzano Apache Hive includono ScanmarQED, EY, Cloudera, IBM, ENSIGN INFOSECURITY (CYBERSECURITY) PTE. LTD., Dice, Royal Bank of Canada, Deutsche Bank, Infogain, JPMorgan Chase Bank, N.A. e molte altre. Puoi trovare un elenco completo di 1,937 aziende che utilizzano Apache Hive su TheirStack.com.
Secondo i nostri dati, Apache Hive è più popolare in Stati Uniti (793 companies), Regno Unito (99 companies), India (95 companies), Spagna (53 companies), Canada (52 companies), Francia (48 companies), Germania (37 companies), Brasile (29 companies), Australia (27 companies), Singapore (22 companies). Tuttavia, è utilizzato da aziende in tutto il mondo.
Puoi trovare aziende che utilizzano Apache Hive cercandolo su TheirStack.com. Tracciamo le offerte di lavoro di milioni di aziende e le utilizziamo per scoprire quali tecnologie e strumenti interni stanno utilizzando.