when to use hbase and when to use hive - Wikitechy https://www.wikitechy.com/interview-questions/tag/when-to-use-hbase-and-when-to-use-hive/ Interview Questions Tue, 14 Sep 2021 12:14:12 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 https://www.wikitechy.com/interview-questions/wp-content/uploads/2025/10/cropped-wikitechy-icon-32x32.png when to use hbase and when to use hive - Wikitechy https://www.wikitechy.com/interview-questions/tag/when-to-use-hbase-and-when-to-use-hive/ 32 32 What is the Relationship Between Hadoop Hbase and Hive ? https://www.wikitechy.com/interview-questions/hive/what-is-the-relationship-between-hadoop-hbase-and-hive/ https://www.wikitechy.com/interview-questions/hive/what-is-the-relationship-between-hadoop-hbase-and-hive/#respond Tue, 13 Jul 2021 21:51:23 +0000 https://www.wikitechy.com/interview-questions/?p=581

Hadoop HBase And Hive

hadoop hbase hive
  • Hadoop is an open source software stack that runs on a cluster of machines.
  • Hadoop provides distributed storage and distributed process for very big data sets.

It has following 2 core components:

HDFS :

  • Hadoop Distributed file system or HDFS is a Java based distributed file system that enables us to store big data across multiple nodes in a Hadoop cluster.
  • So, if you install Hadoop, you will get HDFS as an underlying storage system for storing the big data sets in the distributed environment.

MapReduce:

  • MapReduce is a programming framework for writing applications that method massive amounts of structured and unstructured data in parallel across a cluster of thousands of machines, in a reliable, fault-tolerant manner.

HBase:

  • Apache HBase is Hadoop database, a distributed, scalable, column oriented big data store.
  • HBase is built on top of HDFS means that data you store in HBase is stored in HDFS itself.

Hive:

  • Hive is an important tool for Hadoop ecosystem it provides an SQL for querying data in HDFS, other file systems that integrate with Hadoop like MapR-FS and Amazon’s S3 and databases like HBase(the Hadoop database) and Cassandra.
  • Hive too like HBase stores data into HDFS but it uses MapReduce too. It compiles queries into MapReduce jobs and runs them on the cluster. It was the primary abstraction engines to be built on top of MapReduce. Hive needs a metastore(JDBC compliant RDBMS) to store its metadata.
]]> https://www.wikitechy.com/interview-questions/hive/what-is-the-relationship-between-hadoop-hbase-and-hive/feed/ 0 What is Hbase used for, and what are the benefits that it provides over Pig and Hive ? https://www.wikitechy.com/interview-questions/apache-pig/what-is-hbase-used-for-and-what-are-the-benefits-that-it-provides-over-pig-and-hive/ https://www.wikitechy.com/interview-questions/apache-pig/what-is-hbase-used-for-and-what-are-the-benefits-that-it-provides-over-pig-and-hive/#respond Mon, 12 Jul 2021 07:58:18 +0000 https://www.wikitechy.com/interview-questions/?p=194

Hbase uses

  • HBASE will not replace Map Reduce. It is scalable distributed database.
  • Hbase processing data will act as Map Reduce.
  • The Hadoop database is define Apache HBase.
  • HBase is a sub-project of the Apache Hadoop project and is used to provide real-time read and write access to big data.
  • Hbase is a Bigtable clone.
  • Hbase is a open source.
  • Hbase called as Cascading connector.

what are the Features that it provides over Pig and Hive?

  • Possible to create tables in Hive and store data,it can even map the user’s existing HBase tables to Hive and operate on them.
  • Hive should be used for analyzing query of data collected over a period of time.
  • Hbase has got its own set of very good Application Programming Interface(API) which could be used to push/pull the data.
  • It has a good community for the future.It developed on top if hadoop already used to integration for the Hadoop platform.
  • Hbase can be integrated with MapReduce that can do bulk operation, like indexing, analytics etc.
    • Distributed storage
    • Table-like in data structure
    • multi-dimensional map
    • High scalability
    • High availability
    • High performance
  • A distributed data store that can scale horizontally to 1,000s of commodity servers and petabytes of indexed storage.
  • Designed to operate on top of the Hadoop distributed file system (HDFS) or Kosmos File System (KFS, aka Cloudstore) for scalability, fault tolerance, and high availability.
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