HBase Tutorial
HBase Tutorial
HBase tutorial provides important and advanced HBase concepts. Our tutorial for beginners and professionals designed HBase.
HBase is an open-source platform provided by Apache. It is a sorted map data created on Hadoop. It's column-oriented and horizontally scalable.
Our HBase tutorial involves all the topics of Apache HBase with HBase Data Model, HBase Write, HBase Read, HBase Installation, and HBase MemStore, RDBMS vs HBase, HBase Commands, and HBase Example etc.
What is HBase?
HBase is a Hadoop project, which is an open-source, distributed Hadoop database, which has its genesis in Google's BigTable.
- It has support-programming language in Java
- It is an integral part of the Hadoop community and the Apache Software Foundation.
- It is a high availability database, which exclusively runs on top of the HDFS.
- It is a column-oriented database built on top of HDFS.
Why Apache HBase?
HBase features such as highly fault-tolerant and robust operating with fragmented data and how it can operate on multiple data types, making it useful for diverse business scenarios as well.
- Hadoop's architecture and APIs
- Know how to use Java to write basic applications
- Any database is working knowledge.
Right Audience
- Those who are experts in the design of technology and mainframe.
- Also, project managers, researchers for Big Data as well as experts in the analysis.
- Also, Software Developers and Certified Data Management.
Features of HBase
- Consistency
- Atomic Read and Write
- Sharding
- High Availability
- Client API
- Scalability
- Distributed Storage
- Data Replication
- Hadoop/HDFS integration
- Load Sharing
- API Support
- MapReduce Support
- Real-Time Processing
- Schema-less
- High Throughput
Consistency:-
For high-speed requirements, we can use this HBase feature because it offers consistent reading and writing.
Atomic Read and Write:-
All other processes are stopped from carrying out any read, write operations during one read, or write process, which is what we call Atomic reading and writing.
Sharding:-
HBase provides an automatic and manual division of regions into smaller sub-regions as soon as it reaches a threshold size to minimize I / O time and overhead.
High Availability:-
It also provides LAN and WAN, enabling failover and recovery. Mostly, at heart, a master database manages the monitoring of servers in the area as well as all cluster metadata.Client API:-
It also provides programmatic access through Java APIs.
Scalability:-
HBase supports scalability in both linear and modular form. We can also assume that it is linearly scalable.
Distributed Storage:-
HBase supports this feature-distributed storage like HDFS.
Data Replication:-
HBase supports cluster-wide replication of data.
Hadoop/HDFS integration:-
HBase can run on external file systems as well as compatibility with Hadoop / HDFS.
Failover Support Load Sharing:-
HDFS is internally distributed and automatically recovered by using multiple block allocation and replication, and HBase runs on top of HDFS, thus automatically improving HBase. Such failover is also allowed with the use of RegionServer replication.
API Support:-
According to support for Java APIs in HBase, clients can easily access it.
MapReduce Support:-
HBase supports MapReduce for parallel processing of large data size.
Real-Time Processing:-
HBase supports block cache and Bloom filters for real-time database processing.
Schemaless:-
No fixed column schema specification exists in HBase because it is schema-less. It, therefore, defines only the families of the columns.
High Throughput:-
It provides unparalleled high write throughput due to HBase's high security and simple management features.
Prerequisite
Before learning HBase, you must have basic knowledge of the Hadoop and Java.
Audience
Our HBase tutorial designed to help beginners and professionals alike.
Problem
We assure you that you will not find any problem in this HBase tutorial. But if there is an error, please post the problem in the contact form.