SDMA-FDMA-TDMA-fixed TDM
- 1. HBASE IN BIG DATA ANALYSIS S.AZHAGARAMMAL MSc(IT) Nadar Saraswathi College of Arts and Science, Theni.
- 2. HBase: HBase is an open-source, column-oriented distributed database system in a Hadoop environment. Initially, it was Google Big Table, afterward, it was re-named as HBase and is primarily written in Java. Apache HBase is needed for real-time Big Data applications.
- 3. Apache HBase is needed for real-time Big Data applications. HBase can store massive amounts of data from terabytes to petabytes. The tables present in HBase consists of billions of rows having millions of columns. HBase is built for low latency operations, which is having some specific features compared to traditional relational models.
- 4. HBase Unique Features: HBase is built for low latency operations. HBase is used extensively for random read and write operations. HBase stores a large amount of data in terms of tables. Provides linear and modular scalability over cluster environment. Strictly consistent to read and write operations
- 7. Why Choose HBase A table for a popular web application may consist of billions of rows. If we want to search particular row from such a huge amount of data, HBase is the ideal choice as query fetch time in less.
- 8. Most of the online analytics applications use HBase. Traditional relational data models fail to meet performance requirements of very big databases. These performance and processing limitations can be overcome by Apache HBase.
- 9. HBase different from other NoSQL model: HBase stores data in the form of key/value pairs in a columnar model. In this model, all the columns are grouped together as Column families
- 10. HBase provides a flexible data model and low latency access to small amounts of data stored in large data sets. HBase on top of Hadoop will increase the throughput and performance of distributed cluster set up. In turn, it provides faster random reads and writes operations