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HBase
HBase

193
156
+ 1
12
Riak
Riak

76
71
+ 1
35
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HBase vs Riak: What are the differences?

HBase: The Hadoop database, a distributed, scalable, big data store. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop; Riak: A distributed, decentralized data storage system. Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.

HBase and Riak belong to "Databases" category of the tech stack.

"Performance" is the primary reason why developers consider HBase over the competitors, whereas "High Performance " was stated as the key factor in picking Riak.

HBase and Riak are both open source tools. Riak with 3.24K GitHub stars and 530 forks on GitHub appears to be more popular than HBase with 2.91K GitHub stars and 2.01K GitHub forks.

According to the StackShare community, HBase has a broader approval, being mentioned in 54 company stacks & 18 developers stacks; compared to Riak, which is listed in 15 company stacks and 10 developer stacks.

What is HBase?

Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.

What is Riak?

Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
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      What are some alternatives to HBase and Riak?
      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.
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      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.
      Druid
      Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
      Couchbase
      Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
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      How developers use HBase and Riak
      Avatar of Pinterest
      Pinterest uses HBaseHBase

      The final output is inserted into HBase to serve the experiment dashboard. We also load the output data to Redshift for ad-hoc analysis. For real-time experiment data processing, we use Storm to tail Kafka and process data in real-time and insert metrics into MySQL, so we could identify group allocation problems and send out real-time alerts and metrics.

      Avatar of Axibase
      Axibase uses HBaseHBase
      • Raw storage engine
      • Replication
      • Fault-tolerance
      Avatar of Mehdi TAZI
      Mehdi TAZI uses HBaseHBase

      Range scan and HDFS Buffering system

      Avatar of anerudhbalaji
      anerudhbalaji uses HBaseHBase

      Primary datastore

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