Difference Between Apache Hive and Apache Impala Last Updated : 30 Sep, 2022 Comments Improve Suggest changes Like Article Like Report Apache Hive: It is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Hive gives a SQL-like interface to query data stored in various databases and file systems that integrate with Hadoop. It is an advanced analytics language that would allow you to leverage your familiarity with SQL (without writing MapReduce jobs separately) then Apache Hive is definitely the way to go. HiveQL queries anyway get converted into a corresponding MapReduce job which executes on the cluster and gives you the final output. Hive (and its underlying SQL like language HiveQL) does have its limitations though and if you have a really fine-grained, complex processing requirements at hand you would definitely want to take a look at MapReduce. Apache Impala: It is an open-source massively parallel processing SQL query engine for data stored in a computer cluster running Apache Hadoop. Impala has been described as the open-source equivalent of Google F1, which inspired its development in 2012. Cloudera Impala is an excellent choice for programmers for running queries on HDFS and Apache HBase as it doesn’t require data to be moved or transformed prior to processing. Cloudera Impala easily integrates with the Hadoop ecosystem, as its file and data formats, metadata, security, and resource management frameworks are the same as those used by MapReduce, Apache Hive, Apache Pig, and other Hadoop software. Below is a table of differences between Apache Hive and Apache Impala: S.No.Apache HiveApache Impala1.Hive is perfect for those project where compatibility and speed are equally importantImpala is an ideal choice when starting a new project2.Hive translates queries to be executed into MapReduce jobsImpala responds quickly through massively parallel processing3.Versatile and plug-able languageUsed for brute force processing4.Every hive query has this problem of "cold start"It avoids startup overhead as daemon processes are started at boot time5.It has SQL like queriesIt provides HDFS and apache HBase storage support6.Use familiar built in user defined functions(UFFDs) to manipulate the dataCan easily read metadata using driver and SQL syntax from apache hive7.It is data warehouse infrastructure build over hadoop platformIt doesn't require data to be moved or transformed8.Used for analysis processing and visualizationUsed by programmers for running queries on HDFS and apache HBase9.Apache Hive is fault-tolerant. Apache Impala is not fault tolerant.10.Hive does not support interactive computing.Impala supports interactive computing. Comment More infoAdvertise with us Next Article Difference Between Apache Hive and Apache Impala R rakshitarora Follow Improve Article Tags : Cloud Computing Similar Reads Difference Between Apache Kafka and Apache Flume Apache Kafka: It is an open-source stream-processing software platform written in Java and Scala. It is made by LinkedIn which is given to the Apache Software Foundation. Apache Kafka aims to provide a high throughput, unified, low-latency platform for handling the real-time data feeds. Kafka genera 2 min read Difference Between Apache Hadoop and Apache Storm Apache Hadoop: It is a collection of open-source software utilities that facilitate using a network of many computers to solve problems involving massive amounts of data and computation. 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