HBase is a non-relational column-oriented database, which means HBase doesn’t store relational data. That means HBase doesn’t support SQL for making structured queries to the database so you can actually call HBase a data store instead of a database.
Is HBase NoSQL?
How Does HBase Work?
HBase’s architecture makes it a great database for storing unstructured data. You can access the data in HBase using an HBase API.
In HBase, data lives within individual columns indexed by a unique row key, called the primary key. This type of architecture enables rapid retrieval of the rows and columns you request. In addition, the architecture makes it efficient to scan over a table’s columns. HBase distributes the data and the requests across all the servers in an HBase cluster, which makes it possible to query petabytes of data in a matter of milliseconds.
That said, due to SQL’s popularity, you can integrate an SQL layer called Apache Phoenix on top of your HBase setup. With Phoenix, you can retrieve data from HBase similar to how you’d use SQL to retrieve data from a traditional relational database management system (RDBMS).
What Is HBase Used For?
HBase is ideal for high-scale real-time applications, such as a social media app or a streaming application. Thanks to the lack of a fixed database schema in a non-relational database like HBase, developers can add new data without conforming to a schema model. With a traditional relational database model, one would need to conform to a strict schema model.
It’s common for web application databases to consist of billions of rows of data. To access a random entry in the database, you’ll be looking for a needle in a haystack; you can find it, but it’ll take a long time. Depending on what kind of database management system you’re using, the needle can become much easier to locate. When dealing with large databases, a commonly used RDBMS, such as MySQL, performs poorly because an RDBMS slows down exponentially as the data grows. HBase can help overcome RDBMS performance issues because HBase is designed to handle large chunks of data. With HBase, searching for entries in the database is more efficient than using a regular RDBMS system thanks to the column-oriented non-relational structure of HBase.
What Are the Advantages of HBase?
HBase offers a robust solution for storing big data. You can also store sparse data sets to HBase in a fault-tolerant manner. Moreover, HBase supports streamlined random access to read or write in a large volume of data. In this way, HBase is similar to Google BigTable, which also provides quick random access to high volumes of data.
Finally, HBase is a data store that scales linearly. It’s built of tables that have rows and columns, which makes it similar to a traditional relational database.
What Are the Key Features of HBase?
With HBase, you can scale your applications across thousands of servers because HBase applications scale linearly.
HBase comes with low-latency read and write access to huge amounts of structured, semi-structured and unstructured data. This happens by distributing the data to region servers where each of those servers stores a portion of the table’s data. This makes the data read and write faster than if all the data lived on the same server.
HBase data is split across many hosts in a cluster, thus the system can withstand the failure of an individual host.