APACHE HBASE

What is Apache HBase?

Apache HBase is an open-source, NoSQL, distributed big data store. It enables random, strictly consistent, real-time access to petabytes of data. HBase is very effective for handling large, sparse datasets.

HBase integrates seamlessly with Apache Hadoop and the Hadoop ecosystem and runs on top of the Hadoop Distributed File System (HDFS) or Amazon S3 using Amazon Elastic MapReduce (EMR) file system, or EMRFS. HBase serves as a direct input and output to the Apache MapReduce framework for Hadoop, and works with Apache Phoenix to enable SQL-like queries over HBase tables. 

How does HBase work?

HBase, a NoSQL titan, tackles big data with speed and scale. Data lives in columns, not rows, for lightning-fast searches. Spread across servers, it handles petabytes with ease. Think real-time analytics, vast log files, and lightning-fast recommendations. Open-source and Hadoop-friendly, it conquers big data challenges like a champ. Just remember, relational data takes a backseat here.

Features of Apache Hbase:

1. Highly Scalable: Horizontally scalable across servers, handling petabytes of data with ease.
2. Blazing Fast: Column-oriented architecture and distributed processing accelerate read/write operations.
3. Fault Tolerant: Replication across servers ensures data availability even when failures occur.
4. Real-Time Rockstar: Thrives in real-time scenarios, providing instant access to the latest data.
5. Dynamic Schema: Add or remove columns freely, adapting to evolving data needs.
6. NoSQL Freedom: Flexible for non-relational data, excelling with large, sparse datasets.
7. Hadoop Harmony: Seamless integration with HDFS, MapReduce, and Phoenix for a powerful data stack.
8. Cost-Effective Choice: Open-source and built on HDFS, delivering big data power without massive costs.

APACHE HBASE ARCHITECTURE :

1. HBase area
A range is an ordered range of rows that store data between the start and end keys. A table in HBase is divided into several areas.
The default region size is 256 MB, and we can configure it according to our needs. Region Server has a group of regions for clients. Region Server can serve 1000 regions (approximately) to the client.

2. HBase HMaster
The HMaster in HBase processes the Region Server collection that resides in the DataNode. The HBase HMaster performs DDL operations and assigns regions to region servers. Coordinates and manages the regional server.
HMaster assigns regions to region servers during startup and reassigns regions to region servers during recovery and load balancing. It is responsible for monitoring all Region Server instances in the cluster. It does this with the help of Zookeeper and performs a recovery mechanism if any Region Server fails. HMaster provides an interface for creating, updating and deleting tables.

3. HBase ZooKeeper – Coordinator
The Zookeeper acts as a coordinator in a distributed HBase environment. It helps maintain the server state inside the cluster by communicating through sessions.
Each Region Server and the HMaster server send a continuous heartbeat regularly to Zookeeper. Zookeeper checks which server is active and available. Zookeeper provides notification of server failure so that HMaster can take recovery action. Zookeeper also maintains a path to the.META server. This helps the client search for any region.

4. HBase meta table

META table is a special HBase catalog table that maintains a list of all region servers in the HBase storage system. A . META file manages a table in the form of keys and values. The key will represent the initial key of the HBase region and its id. The value will contain the path to the region server.

Advantages:

1. Massive Data Handling: Crunch petabytes of data with ease, perfect for massive log files, time-series data, and large analytical datasets.
2. Speed Demon: Navigate data at lightning speed, thanks to the column-oriented architecture and distributed processing. Say goodbye to sluggish queries.
3. Built for Scale: Add more servers to your cluster as your data grows, keeping HBase flexible and adaptable to your needs.
4. Fault Tolerance: Don't sweat single server failures. HBase replicates data across servers, ensuring continuous access even when things go wrong.
5. Real-Time Rockstar: Need instantaneous data insights? HBase thrives in real-time scenarios, giving you immediate access to the latest information.
6. No Schema Strictures: Embrace flexibility. HBase's dynamic schema lets you add and remove columns freely, adapting to your evolving data needs.

Disadvantages:

1.  No SQL Nirvana: If you crave the familiar logic and structure of relational databases, HBase's NoSQL nature might feel like a foreign language. Complex joins and transactions pose challenges.
2. Complexity Curve: Setting up and managing an HBase cluster requires dedicated expertise. It's not as straightforward as managing traditional relational databases.
3. Limited Querying: While fast for specific data retrieval, HBase's lack of native SQL and limited indexing options can make complex queries clunky and resource-intensive.
4. Single Master Bottleneck: The HMaster plays a critical role, and its failure can cause temporary service disruptions. Consider high-availability setups to mitigate this risk.
5. Not for Transactions: HBase prioritizes speed and scalability over ACID transactions. If data consistency across multiple operations is crucial, HBase might not be the best fit.
6. Memory and CPU Hungry: The in-memory MemStore and distributed nature can be demanding on resources, especially with large datasets or frequent writes.

Conclusion:

We can say that Apache HBase is a NoSQL database that runs on top of the Hadoop Distributed File System. Provides the BigTable functionality of the Hadoop framework. It consists of HMaster Server, HBase Region Server, and Regions and Zookeeper. The article included the difference between HBase and RDBMS as well as the difference between HBase and HDFS. HBase provides consistent reads and writes. It is open-source and scalable. We can use HBase in many industries, including medicine, sports, e-commerce, etc.