hive vs hbase vs pig - Wikitechy https://www.wikitechy.com/interview-questions/tag/hive-vs-hbase-vs-pig/ Interview Questions Tue, 14 Sep 2021 12:14:12 +0000 en-US hourly 1 https://wordpress.org/?v=6.9 https://www.wikitechy.com/interview-questions/wp-content/uploads/2025/10/cropped-wikitechy-icon-32x32.png hive vs hbase vs pig - Wikitechy https://www.wikitechy.com/interview-questions/tag/hive-vs-hbase-vs-pig/ 32 32 What is the relationship between Apache Hadoop, HBase, Hive and Cassandra ? https://www.wikitechy.com/interview-questions/cassandra/what-is-the-relationship-between-apache-hadoop-hbase-hive-and-cassandra/ https://www.wikitechy.com/interview-questions/cassandra/what-is-the-relationship-between-apache-hadoop-hbase-hive-and-cassandra/#respond Tue, 13 Jul 2021 05:25:21 +0000 https://www.wikitechy.com/interview-questions/?p=436

Apache Hadoop:

  • It is a Big Data framework which uses Hadoop Distributed File System to Store the data and MapReduce framework to process that data. Java is used as native language to write MapReduce programs.
  • Apache Hbase and Cassandra are both NoSQL databases.
  • It does not maintain the strict ACID transactions and require better data modelling to be used effectual.
  • Their presentation can be calculated by benchmarking the database using a tool called YCSB(Yahoo Cloud Serving Benchmark).
  • Factors examine in benchmarking can be read, write ,read-modify-write latency in executing queries.
Hbase:
  • It is a Master -Slave NoSQL database dependent upon Hadoop cluster .
  • It is good for Heavy reads and less Write applications
apache hadoop ecosystem

Apache Cassandra:

  • It is a master less and shared-nothing, ring based architecture which does not depend upon Hadoop framework.
  • It is good for Write heavy and less read applications.

Apache Hive:

  • It is a collective processing framework to process the data using a language called Hive Query Language(HQL).
  • HQL is a sql wrapper on top of HDFS which protect writing Mapreduce programs in Java.
  • Instead one can use SQL like language to do their daily tasks.
  • Apache Hive is mainly used for ETL and data warehousing feature in Hadoop.
  • The process of hive is to create tables, joins, unions, aggregates etc. It develop visualization reports can be done by Tableau.
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Difference between Hive and HBase ?

Hive

  • Hive is a datawarehousing package built on the top of Hadoop. It is mainly used for data analysis. It generally target towards users already comfortable with Structured Query Language (SQL).
  • It is similar to SQL and called Hive Query Language (HQL).
  • Hive manages and queries structured data. Moreover, hive abstracts complexity of Hadoop. It does not support
    • Not a full database.
    • Not a real time processing system.
    • Not SQL-92 compliant.
    • Does not provide row level insert, updates or deletes.
    • Doesn’t support transactions and limited sub-query support.
    • Query optimization in evolving stage.

Hbase

  • HBase is a column-oriented database management system that runs on top of Hadoop Distributed File System (HDFS).
  • It is well suited for sparse data sets, which are common in many Big Data use cases.
  • It is an opensource, distributed database developed by Apache software foundations.
  • Initially, it was named Google Big Table, afterwards it was re-named as HBase and is primarily written in Java.
  • It can store massive amount of data from terabytes to petabytes.
  • It is built for low-latency operations and is used extensively for read and write operations.
  • It stores large amount of data in the form of tables.
Difference between HIVE and HBASE
HIVE HBASE
Hive is a query engine. Data storage particularly for unstructured data.
Mainly used for batch processing. Extensively used for transactional processing.
Not a real time processing. Real-time processing.
Only for analytical queries. Real-time querying.
Runs on the top of Hadoop. Runs on the top of HDFS (Hadoop distributed file system).
Apache Hive is not a database. It support NoSQL database.
It has schema model. It is free from schema model.
Made for high latency operations. Made for low level latency operations.
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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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