HBase is an open-source, non-relational, distributed database from the Apache stack which was modeled after Google's Bigtable. This column-oriented database management system runs on top of HDFS (Hadoop Distributed File System) and provides a fault-tolerant way of storing large quantities of sparse data. This blog offers an introduction to Apache HBase for those who wish to grab lucrative jobs in the Big Data Hadoop world.
- Updated on: 20th Jun, 14
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It isn’t uncommon to find ourselves looking for a particular piece of paper in a pile of rubble on our desk. Needless to say, with digitized big data, the amount of rubble is welling up in billions, and looking for some specific information in this pile is no less than looking for a needle in a giant haystack. When we consider such large and massive amounts of data, a convenient database is definitely required, something that allows us to organize the data into groups for easier access.
HBase is a column-oriented database management system. It’s an open-source implementation of Google’s Bigtable storage architecture, and it runs on top of HDFS (Hadoop Distributed File System). It is well suited for thin datasets, which happens to be pretty common in many cases of big data usage. In contrast with the typical fellow database systems, HBase isn’t a relational data store at all, and it does not support a structured query language. Much like a typical MapReduce application, HBase applications are written in Java, but they also support writing applications in Avro, REST, and Thrift. In recent times, HBase’s performance has improved a great deal, and it serves several data-driven websites, including Facebook’s messaging platform. However, it still isn’t considered a direct replacement for an SQL database.
HBase can manage structured and semi-structured data and has some built-in features such as scalability, versioning, compression, and garbage collection. It can provide fault-tolerance and quick recovery from individual server failures as it uses write-ahead logging and distributed configuration. HBase is built on top of Hadoop/HDFS, and the data stored in HBase can be manipulated using Hadoop’s MapReduce capabilities.
Cloudera Enterprise, with its Flex Edition or Data Hub Edition, helps take control of the power of Apache HBase in production environments. And, it is imperative for students to take Hadoop courses before turning his or her attention to HBase. Although there are several HBase and Hadoop courses available online and there are books on these subjects, perhaps, the best way to learn HBase would be with Intellipaat as it provides a definitive HBase Training which gives gradual step-by-step explanation of the workings of the technology. It also provides knowledge on how to practically work with HBase with its easy-to-understand hands-ons. Additionally, Intellipaat also offers unique industry-designed Hadoop and Cloudera courses.
Basically, HBase gracefully simplifies large amounts of data into a convenient source for future use. It is a huge time saver as one of its functions is to filter out the irrelevant and garbage data and return data that is necessary. It is designed in a way to store denormalized data, contain wide and sparsely populated tables, and support automatic partitioning.