Cassandra vs. Hadoop vs. RocksDB

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Cassandra

Hadoop

RocksDB

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57

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45

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8

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GitHub Stats

Description

What is Cassandra?

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

What is Hadoop?

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

What is RocksDB?

RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

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Why do you like Hadoop?

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Why do you like RocksDB?

Cons about this tool

Cons
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No Cons submitted yet for Hadoop
Cons
No Cons submitted yet for RocksDB

Companies

278 Companies Using Cassandra
208 Companies Using Hadoop
4 Companies Using RocksDB

Integrations

Cassandra Integrations
Hadoop Integrations
No integrations listed yet

Latest News

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Cassandra Query Language
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How to Get Hadoop Data into a Python Model
Elasticsearch for Apache Hadoop 6.0.0 GA is Released
All things RocksDB at Percona Live Europe 2017


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