hbase vs cassandra - Wikitechy

What is the difference between Cassandra and Hadoop ?

Editor — Tue, 13 Jul 2021 05:44:49 +0000

Parameters	Cassandra	Hadoop
CAP theorem	AP	CP
Architecture	All nodes are same in Peer-to-Peer Distributed architecture.	Master/Slave. Name Node act as Master and data node act as worker node.
Read and Write Design	Read and write anywhere model.	Write once read many access models.
Area of utilization	Real time online transactional processing	Batch-oriented analytical solutions.
Mode of accessing data	Cassandra query language and Command line interface tools.	Map/Reduce for read/write operations.
Data storage model	Keys space column family to store the data and introduces primary and secondary indexes for high availability of data	File system. Large files are destroyed into small piece and copy on many data node
Fault tolerance	High availability- NO SPOF cluster all nodes are same and experienced to handle the access	when master node is down if the Single point of failure Vulnerable to be failed.
Storage schema	Combines schema from Google big table and Amazon Dynamo	Physical file system schema.
Communication	Gossip protocol	RPC/TCP and UDP

Editor — Tue, 13 Jul 2021 05:25:21 +0000

It is a Big Data framework which uses Hadoop Distributed File System to Store the data and MapReduce framework to process that data. Java is used as native language to write MapReduce programs.
Apache Hbase and Cassandra are both NoSQL databases.
It does not maintain the strict ACID transactions and require better data modelling to be used effectual.
Their presentation can be calculated by benchmarking the database using a tool called YCSB(Yahoo Cloud Serving Benchmark).
Factors examine in benchmarking can be read, write ,read-modify-write latency in executing queries.

Hbase:

It is a master less and shared-nothing, ring based architecture which does not depend upon Hadoop framework.
It is good for Write heavy and less read applications.

It is a collective processing framework to process the data using a language called Hive Query Language(HQL).
HQL is a sql wrapper on top of HDFS which protect writing Mapreduce programs in Java.
Instead one can use SQL like language to do their daily tasks.
Apache Hive is mainly used for ETL and data warehousing feature in Hadoop.
The process of hive is to create tables, joins, unions, aggregates etc. It develop visualization reports can be done by Tableau.

Editor — Mon, 12 Jul 2021 19:23:16 +0000

What are the features of Apache HBase

- Linear and modular scalability.
- Strictly consistent reads and writes.
- Automatic and configurable sharding of tables.
- Automatic failover support between RegionServers.

- Convenient base classes for backing Hadoop MapReduce jobs with Apache HBase tables.
- Easy to use Java API for client access.
- Block cache and Bloom Filters for real-time queries.
- Query predicate push down via server side Filters.
- Thrift gateway and an REST-ful Web service that supports XML, Protobuf, and binary data encoding options.

How to use Apache HBase REST Interface

Extensible JRuby-based (JIRB) shell.
Support for exporting metrics via the Hadoop metrics subsystem to files or Ganglia; or via JMX.