Hbase is an open source and sorted map data built on Hadoop. It is column oriented and horizontally scalable.
It is based on Google's Big Table.It has set of tables which keep data in key value format. Hbase is well suited for sparse data sets which are very common in big data use cases. Hbase provides APIs enabling development in practically any programming language. It is a part of the Hadoop ecosystem that provides random real-time read/write access to data in the Hadoop File System.
Why HBase
- RDBMS get exponentially slow as the data becomes large
- Expects data to be highly structured, i.e. ability to fit in a well-defined schema
- Any change in schema might require a downtime
- For sparse datasets, too much of overhead of maintaining NULL values
Features of Hbase
- Horizontally scalable: You can add any number of columns anytime.
- Automatic Failover: Automatic failover is a resource that allows a system administrator to automatically switch data handling to a standby system in the event of system compromise
- Integrations with Map/Reduce framework: Al the commands and java codes internally implement Map/ Reduce to do the task and it is built over Hadoop Distributed File System.
- sparse, distributed, persistent, multidimensional sorted map, which is indexed by rowkey, column key,and timestamp.
- Often referred as a key value store or column family-oriented database, or storing versioned maps of maps.
- fundamentally, it's a platform for storing and retrieving data with random access.
- It doesn't care about datatypes(storing an integer in one row and a string in another for the same column).
- It doesn't enforce relationships within your data.
- It is designed to run on a cluster of computers, built using commodity hardware.
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