{"id":9856,"date":"2018-03-03T13:49:12","date_gmt":"2018-03-03T13:49:12","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=9856"},"modified":"2018-03-03T13:49:12","modified_gmt":"2018-03-03T13:49:12","slug":"hbase-vs-hive","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/hbase-vs-hive\/","title":{"rendered":"HBase vs Hive : Feature Wise Difference between Hive vs HBase"},"content":{"rendered":"

Both Apache Hive and HBase are Hadoop<\/strong> based\u00a0Big Data<\/strong> technologies. Also, both serve the same purpose that is to query data. However, Apache Hive and HBase both run on top of Hadoop still they differ in their functionality.\u00a0<\/span><\/p>\n

So, in this blog “HBase vs Hive”, we will understand the difference between Hive and HBase. Moreover, we will compare both technologies on the basis of several features. But before going directly into hive and HBase comparison, we will introduce both Hive and HBase individually.<\/span><\/p>\n

So, let’s start HBase vs Hive.<\/p>\n

Difference Between HBase vs Hive<\/span><\/h2>\n

i. What is Apache Hive?<\/span><\/h3>\n

Initially, Hive was developed by Facebook. Afterward, it is under the Apache software foundation. Moreover, it is an open source data warehouse. <\/span><\/p>\n

Also, we use it for analysis and querying datasets. Moreover, it is developed on top of Hadoop<\/strong> as its data warehouse framework for querying and analysis of data is stored in HDFS<\/strong>.<\/span>
\n<\/span>
\n<\/span>In addition, it is useful for performing several operations. Such as data encapsulation, ad-hoc queries, & analysis of huge datasets. Moreover, for managing and querying structured data Hive’s design reflects its targeted use as a system.<\/span><\/p>\n

ii. What is HBase?<\/span><\/h3>\n

HBase is a non-relational column-oriented distributed database. Basically, it runs on the top of HDFS. Moreover, it is a NoSQL open source database that stores data in rows and columns. However, Cell is the intersection of rows and columns.<\/span><\/p>\n

HBase vs Hive<\/span><\/h2>\n

Following points are feature wise comparison of\u00a0HBase vs Hive.<\/p>\n

\"Hive<\/a>

Feature Wise Comparison – HBase vs Hive<\/p><\/div>\n

i. Database type<\/h3>\n
    \n
  • Apache Hive<\/strong><\/li>\n<\/ul>\n

    Basically, Apache Hive is not a database.<\/span><\/p>\n

      \n
    • HBase<\/strong><\/li>\n<\/ul>\n

      HBase does support NoSQL database.<\/span><\/p>\n

      ii. Type of processing<\/span><\/h3>\n
        \n
      • Apache Hive<\/strong><\/li>\n<\/ul>\n

        Hive does support Batch processing. That is OLAP.<\/span><\/p>\n

          \n
        • HBase<\/strong><\/li>\n<\/ul>\n

          HBase does support real-time data streaming. That is OLTP.<\/span><\/p>\n

          iii. Data Schema<\/span><\/h3>\n
            \n
          • Apache Hive<\/strong><\/li>\n<\/ul>\n

            Basically, it supports to have schema model.<\/span><\/p>\n

              \n
            • HBase<\/strong><\/li>\n<\/ul>\n

              However, it is schema-free.<\/span><\/p>\n

              iv. Latency<\/span><\/h3>\n
                \n
              • Apache Hive<\/strong><\/li>\n<\/ul>\n

                Apache Hive has high latency as compared to HBase.<\/p>\n

                  \n
                • HBase<\/strong><\/li>\n<\/ul>\n

                  As compared to Hive, Hbase have low latency.<\/span><\/p>\n

                  v. Cost<\/span><\/h3>\n
                    \n
                  • Apache Hive<\/strong><\/li>\n<\/ul>\n

                    When compared to HBase, it is more costly.<\/span><\/p>\n

                      \n
                    • HBase<\/strong><\/li>\n<\/ul>\n

                      It is cost-effective while compared to Apache Hive.<\/span><\/p>\n

                      vi. Database model<\/span><\/h3>\n
                        \n
                      • Apache Hive<\/strong><\/li>\n<\/ul>\n

                        Its DataBase model is a relational DBMS<\/strong>.<\/span><\/p>\n

                          \n
                        • HBase<\/strong><\/li>\n<\/ul>\n

                          Its DataBase model is wide column store<\/span><\/p>\n

                          vii. SQL Support<\/span><\/h3>\n
                            \n
                          • Apache Hive<\/strong><\/li>\n<\/ul>\n

                            Hive uses HQL(Hive query language)<\/span><\/p>\n

                              \n
                            • HBase<\/strong><\/li>\n<\/ul>\n

                              It does not use SQL<\/strong><\/span><\/p>\n

                              Viii. Partition methods<\/span><\/h3>\n
                                \n
                              • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                Hive uses sharding method for partition<\/span><\/p>\n

                                  \n
                                • HBase<\/strong><\/li>\n<\/ul>\n

                                  Similarly, HBase also uses sharding method for partition<\/span><\/p>\n

                                  ix. Consistency Level<\/span><\/h3>\n
                                    \n
                                  • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                    Hive is eventual consistent in nature<\/span><\/p>\n

                                      \n
                                    • HBase<\/strong><\/li>\n<\/ul>\n

                                      While HBase is immediate consistent in nature<\/span><\/p>\n

                                      x. When to use<\/span><\/h3>\n
                                        \n
                                      • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                        While we do not want to write complex MapReduce<\/strong> code, we use Apache Hive.<\/span><\/p>\n

                                          \n
                                        • HBase<\/strong><\/li>\n<\/ul>\n

                                          Similarly, while we want to have random access to read and write a large amount of data, we use HBase.<\/span><\/p>\n

                                          xi. Secondary indexes<\/span><\/h3>\n
                                            \n
                                          • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                            No support for secondary indexes.<\/span><\/p>\n

                                              \n
                                            • HBase<\/strong><\/li>\n<\/ul>\n

                                              It does support secondary indexes.<\/span><\/p>\n

                                              xii. Replication Methods<\/span><\/h3>\n
                                                \n
                                              • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                                Hive have selectable replication factor<\/span><\/p>\n

                                                  \n
                                                • HBase<\/strong><\/li>\n<\/ul>\n

                                                  As similar as Hive, it also has selectable replication factor<\/span><\/p>\n

                                                  xiii. Examples<\/span><\/h3>\n
                                                    \n
                                                  • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                                    For Hive, Hubspot is an example.<\/span><\/p>\n

                                                      \n
                                                    • HBase<\/strong><\/li>\n<\/ul>\n

                                                      For HBase, Facebook is the best example.<\/span><\/p>\n

                                                      Usage – HBase vs Hive<\/span><\/h2>\n
                                                        \n
                                                      • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                                        i. We can use Hive while we are familiar with SQL queries and concepts.
                                                        \nii. While we perform analytical querying of historical data<\/span>
                                                        \niii. For Hive to fully unleash its processing and analytical prowess it is important to have structured data.<\/span>
                                                        \niv. However, Hive does not support Real-time analysis. So, HBase is the alternative for real-time analysis.<\/span>
                                                        \nv. Especially, for data analysts<\/span><\/p>\n

                                                          \n
                                                        • HBase<\/strong><\/li>\n<\/ul>\n

                                                          i.\u00a0While we have a large amount of data.
                                                          \nii. It requires ACID properties, although they are not mandatory.<\/span>
                                                          \niii. While Data model schema is sparse.<\/span>
                                                          \niv. Also, while we need to scale applications gracefully.<\/span><\/p>\n

                                                          Companies Using Hive and HBase<\/span><\/h2>\n
                                                            \n
                                                          • Apache Hive<\/strong><\/li>\n<\/ul>\n

                                                            While it comes to market share, has approximately 0.3% of the market share. That means 1902 companies are already using Apache Hive in production. Like:<\/span><\/p>\n

                                                            i. For ad-hoc querying, data mining<\/strong> and for user-facing analytics, \u201cScribd\u201d uses Hive.<\/span>
                                                            \nii. For near real-time web analytics, Hive is an integral part of the Hadoop pipeline at \u201cHubspot\u201d.<\/span>
                                                            \niii. For data mining<\/strong> and analysis of its 435 million global user base, \u201cChitika\u201d, the popular online advertising network uses Hive.<\/span><\/p>\n

                                                              \n
                                                            • HBase<\/strong><\/li>\n<\/ul>\n

                                                              Here, also HBase has a huge market share. That is about 9\/1%. Hence, it means approximately 6190 companies use HBase. Basically, for time series analysis or for clickstream data storage and analysis Companies uses HBase.<\/span><\/p>\n

                                                              i. To store massive databases for the internet and its users, Originally HBase used at \u201cGoogle\u201d.<\/span>
                                                              \nii. \u00a0For real-time analytics, counting Facebook likes and for messaging, \u201cFacebook\u201d uses HBase.<\/span>
                                                              \niii. To store all the trading graphs, \u201cFINRA\u201d Financial Industry Regulatory Authority uses HBase.<\/span>
                                                              \niv. For storing the graph data, \u201cPinterest\u201d uses HBase.<\/span>
                                                              \nv. To personalize the content feed for its users, \u201cFlipboard\u201d uses HBase.<\/span><\/p>\n

                                                              So, this was all in HBase vs Hive. Hope you like our explanation.<\/p>\n

                                                              Conclusion<\/span><\/h2>\n

                                                              Hence, we have seen HBase vs Hive in detail, both are different technologies. Both offer different functionalities where Hive works by using SQL language and it can also be called as HQL and HBase use key-value pairs to analyze the data. Moreover, Hive and HBase work better together. <\/span><\/p>\n

                                                              Since Hive has low latency and can process a huge amount of data, still it cannot maintain up-to-date data. Whereas HBase doesn\u2019t support analysis of data but supports row-level updates on a large amount of data. <\/span><\/p>\n

                                                              However, we have learned a complete comparison between HBase vs Hive. Still, if any query occurs feel free to ask in the comment section.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

                                                              Both Apache Hive and HBase are Hadoop based\u00a0Big Data technologies. Also, both serve the same purpose that is to query data. 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