Hadoop is one of the most preferred Architectures to build Bigdata applications. There are many different tools used by offshore developers as well as outsourcing companies to develop Bigdata applications.
Some of the most famous Hadoop tools are mentioned below.
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Hadoop distributed file system
HDFS is a tool which is used specifically for those systems where a huge amount of data is to be stored as well as streamed across the high bandwidth. To handle such a huge clusters or packets of data we need to have powerful servers which can handle such a high flow of data. Transferring such a huge amount of data saves a lot of time as well as money.
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Hbase
HBase runs on top of HDFS which is a good example of column-oriented DMS. It is also a good tool which can handle a huge amount of data in many clusters. Unlike SQL which is a relational database system, HBase does not support a well-structured query language. The code in HBase is written like a MapReduce algorithm in Java. Hbase is Scalable and linear. It has built-in Java API for the access of client.
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Hive
If we have large datasets located in a distributed storage facility we use Apache Hive. The language that is used in Hive is similar to SQL, and hence, it is known as HiveQL. Indexing is very easy in Hive. It includes bitmap index of 0.10. The data using Hive can be stored in various file formats such as HBase, ORC, RCFile, etc. There are built-in user-defined functions in Hive which can be used to perform small tasks.
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Sqoop
The term Sqoop has arrived from SQL + Hadoop. As the name suggests, it is used to transfer data from any relational database such as SQL to Hadoop or vice-versa. We can also use it to import data from the database management system. Using this tool, we can extract the tool, and at the same time, we can also make changes in the code using Hadoop and then re-upload it using the same tool.
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Pig
Pig is a tool used to analyze larger datasets written in a high-level language. To show data analyze programs. One of the salient features of Pig is that it can handle large datasets parallelly. It is very easy to program as the language that is used in Pig is close to a textual language called PigLatin.
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ZooKeeper
Being a centralized service ZooKeeper helps in maintaining configuration information, providing distributed synchronization, providing group services and naming. All of the above applications are used in distributed applications. Compared to other tools ZooKeeper is a bit difficult to implement.
Emily Butler 