Best Features of HBase | Why HBase is Used?
In our last HBase tutorial, we learned HBase Pros and Cons. Today, we will discuss the basic features of HBase. Moreover, we will also see what makes HBase so popular. So, the answer to this question is “Features of HBase”.
As we all know, HBase is a column-oriented database that provides dynamic database schema. Mainly it runs on top of the HDFS and also supports MapReduce jobs. Moreover, for data processing, HBase also supports other high-level languages.
There are some special features of Apache HBase, which makes it special, such as, Consistency, High Availability and many more. So, in this article “Best Features of HBase”, let’s learn all these Features of HBase in detail.
So, let’s start features of HBase.
What are the Features of HBase?
Below discussed are some main HBase features, let’s discuss them:
We can use this HBase feature for high-speed requirements because it offers consistent reads and writes.
ii. Atomic Read and Write
During one read or write process, all other processes are prevented from performing any read or write operations this is what we call Atomic read and write. So, HBase offers atomic read and write, on a row level.
In order to reduce I/O time and overhead, HBase offers automatic and manual splitting of regions into smaller subregions, as soon as it reaches a threshold size.
iv. High Availability
Moreover, it offers LAN and WAN which supports failover and recovery. Basically, there is a master server, at the core, which handles monitoring the region servers as well as all metadata for the cluster.
v. Client API
Through Java APIs, it also offers programmatic access.
In both linear and modular form, HBase supports scalability. In addition, we can say it is linearly scalable.
vii. Hadoop/HDFS integration
HBase can run on top of other file systems as well as like Hadoop/HDFS integration.
viii. Distributed storage
This feature of HBase supports distributed storage such as HDFS.
ix. Data Replication
HBase supports data replication across clusters.
x. Failover Support and Load Sharing
By using multiple block allocation and replications, HDFS is internally distributed and automatically recovered and HBase runs on top of HDFS, hence HBase is automatically recovered. Also using RegionServer replication, this failover is facilitated.
xi. API Support
Because of Java APIs support in HBase, clients can access it easily.
xii. MapReduce Support
For parallel processing of large volume of data, HBase supports MapReduce.
xiii. Backup Support
In HBase “Backup support” means it supports back-up of Hadoop MapReduce jobs in HBase tables.
xiv. Sorted Row Keys
It is possible to build an optimized request Since searching is done on the range of rows, and HBase stores row keys in lexicographical orders, hence, by using these sorted row keys and timestamp we can build an optimized request.
xv. Real-time Processing
In order to perform real-time query processing, HBase supports block cache and Bloom filters.
xvi. Faster Lookups
While it comes to faster lookups, HBase internally uses Hash tables and offers random access, as well as it stores the data in indexed HDFS files.
xvii. Type of Data
For both semi-structured as well as structured data, HBase supports well.
There is no concept of fixed columns schema in HBase because it is schema-less. Hence, it defines only column families.
xix. High Throughput
Due to high security and easy management characteristics of HBase, it offers unprecedented high write throughput.
xx. Easy to use Java API for Client Access
While it comes to programmatic access, HBase offers easy usage Java API.
xxi. Thrift gateway and a REST-ful Web services
For non-Java front-ends, HBase supports Thrift and REST API.
So, this was all about HBase Features. Hope you like our explanation.
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Conclusion – Features of HBase
Hence, in this HBase tutorial, we have seen all the best features which make HBase so popular. However, to learn more about HBase, keep visiting Dataflair. Still, if any doubt regarding features of HBase, ask in the comment tab.