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HBase vs Vitess: What are the differences?

What is 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.

What is Vitess? It is a database clustering system for horizontal scaling of MySQL. It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.

HBase and Vitess can be categorized as "Databases" tools.

HBase is an open source tool with 2.91K GitHub stars and 2.01K GitHub forks. Here's a link to HBase's open source repository on GitHub.

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    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 Vitess?

    It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use HBase?
    What companies use Vitess?
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    What tools integrate with HBase?
    What tools integrate with Vitess?

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    Blog Posts

    Jun 24 2020 at 4:42PM

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    Amazon S3KafkaHBase+4
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    What are some alternatives to HBase and Vitess?
    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.
    Google Cloud Bigtable
    Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
    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.
    See all alternatives