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The Best Database Platforms To Cater To Big Data Requirements

Billy KE

March. 12, 2020

Today several databases cater to the big data world. It is always a good start with the essential know-how. Users have an online application to seek transaction assistance along with concurrency control. 
This application provided a balanced update and can process the data size of terabytes. The names to count on are:
RDMS
The platform makes use of a B-Tree structure as data engine storage! The index and data get arranged with B-Tree concepts and writes/reads with logarithmic time.  And based on that, for close to a million records, the platform takes about 20 comparisons in the B-Tree, for finding the data in the index. If there are the necessary optimizations, then the comparisons can reduce to three.
MongoDB
You can use this platform if you need to de-normalize the tables. It’s is apt if you want to resort to documents that comprise all the allied nested structures in a single document for maintaining consistency. This platform makes use of the indexes along with the B-Tree architecture, and the file mappings get stored in the memory. It helps fast access to data. The writing takes place, and then the memory data gets flushed at regular intervals.
Cassandra
This database platform is perfect for upfront queries and fast writing! However, the query performance is slightly less, and that makes it ideal for the Time-Series data. Cassandra uses the Long-Structured-Merge-Tree format in the storage engine. Here it starts to write against the memory and then flushes the same to the disk. Cassandra helps in faster writing in comparison to the RDMS and a couple of NoSQL database platforms.
HBASE
This data management platform has similarities with Cassandra in its formatting! HBase also comes with the same performance metrics as Cassandra. Have you already invested in Hadoop? If yes, then you can use this database platform. The primary use of this platform is the lookups.
-CIO East Africa
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