Hadoop Ecosystem Applications

In this article, we will discuss some commonly used applications of Hadoop Ecosystem in brief based on the following steps of bigdata lifecycle:

1. Ingest Data
2. Store Data
3. Analyse Data
4. Access Data

Ingest Data:

FLUME

• Collects, aggregates and transfers big data
• Has a simple and flexible architecture based on streaming data flows
• Uses a simple extensible data model that allows for online analytic application

SQOOP

• Designed to transfer data between relational database system and Hadoop
• Accesses the database to understand the schema of the data
• Generates a MapReduce application to import or export the data

Store Data:

HBASE

• A non-relational database that runs on top of HDFS
• Provides real time wrangling on data
• Stores data as indexes to allow for random and faster access to data

CASSANDRA

• A scalable, NOSQL database designed to have no single point of failure

Analyse Data:

PIG

• Analyses large amounts of data
• Operates on the client side of a cluster
• A procedural data flow language

HIVE

• Used for creating reports
• Operates on the server side of a Cluster
• A declarative programming language

Access Data:

IMPALA

• Scalable and easy to use platform for everyone
• No programming skills are required to use this

HUE

• It stands for Hadoop User Experience
• Allows you to upload, browse and query data
• Runs Pig jobs and workflows
• Provides editors for several SQL query languages like Hive and MYSQL