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Cassandra
Cassandra

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Cassandra vs HBase: What are the differences?

Developers describe Cassandra as "A partitioned row store. Rows are organized into tables with a required primary key". 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. On the other hand, HBase is detailed as "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.

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

"Distributed" is the top reason why over 96 developers like Cassandra, while over 7 developers mention "Performance" as the leading cause for choosing HBase.

Cassandra and HBase are both open source tools. Cassandra with 5.27K GitHub stars and 2.35K forks on GitHub appears to be more popular than HBase with 2.91K GitHub stars and 2.01K GitHub forks.

Uber Technologies, Facebook, and Spotify are some of the popular companies that use Cassandra, whereas HBase is used by Pinterest, HubSpot, and Yammer. Cassandra has a broader approval, being mentioned in 342 company stacks & 239 developers stacks; compared to HBase, which is listed in 54 company stacks and 18 developer stacks.

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 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.
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      What are some alternatives to Cassandra and HBase?
      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.
      Redis
      Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
      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.
      MySQL
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      PostgreSQL
      PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
      See all alternatives
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      How developers use Cassandra and HBase
      Avatar of Soundcloud
      Soundcloud uses CassandraCassandra

      Stitch is a wrapper around a Cassandra database. It has a web application that provides read-access to the counts through an HTTP API. The counts are written to Cassandra in two distinct ways, and it's possible to use either or both of them:

      • Real-time: For real-time updates, Stitch has a processor application that handles a stream of events coming from a broker and increments the appropriate counts in Cassandra.

      • Batch: The batch part is a MapReduce job running on Hadoop that reads event logs, calculates the overall totals, and bulk loads this into Cassandra.

      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 Vital Labs, Inc.
      Vital Labs, Inc. uses CassandraCassandra

      Cassandra is our data management workhorse. It handles all our key-value services, supports time-series data storage and retrieval, securely stores all our audit trails, and backs our Datomic database.

      Avatar of SocialCops
      SocialCops uses CassandraCassandra

      While we experimented with Cassandra in the past, we are no longer using it. It is, however, open for consideration in future projects.

      Avatar of ShareThis
      ShareThis uses CassandraCassandra

      We are using Cassandra in a few of our apps. One of them is as a count service application to track the number of shares, clicks.. etc

      Avatar of Kaiko
      Kaiko uses CassandraCassandra
      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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