Querying, summarizing, exploring, analyzing and retrieving specific data from large data sets made simpler with Apache Hive services.
Hidden Brains is Apache Hive development partner that allows enterprises to undertake advanced work on Apache Hadoop Distributed File System and MapReduce.
Our Hive development and integration solutions are built to allow SQL developers to write Hive Query Language (HQL) statements that are quite similar to standard SQL ones.
We aim to bring the familiarity of relational technology to big data processing using HQL and other structures and operations of relational databases.
We provide better management and querying for large data sets of distributed storage through a range of services.
Hive Solutions Integration
Hive Solutions Customization
Hive Solutions Upgradation
The data of HBase is always available and accessible as there are multiple copies of data that get accessed from another path in cases of hardware failure.
Data in HBase is synced in cluster across the data center. This helps in fault tolerance mechanism as when one node is down, data can be recovered from other nodes.
Due to continuous replication of data in the cluster in HBase, user can be assured of accessing or recovering the data any time without any machine dependency.
Apache HBase supports distributed storage of Hadoop Distributed File System (HDFS) to account for high reliability, scalability and all time availability.
Apache Hive and HBase both support scalability in linear as well as modular form. Hive solutions are highly scalable to accommodate future requirements.
Conceptualize and Deploy Advanced Data Analytics Solutions
We assist enterprises to upgrade their existing Apache Hive with minimum hassle and absolutely no risk of data loss.
We customize and optimize layouts, web graphics and web content to make your Apache Hive solutions more appealing.
We seamlessly integrate Apache Hive solutions with other business processes to account for smooth information exchange.
We use resource manager that allows Hive Metastore to be used across engines of Spark, Presto and Hive.