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HBase
HBase

193
156
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12
Vitess
Vitess

6
8
+ 1
0
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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鈥檚 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.

- No public GitHub repository available -

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鈥檚 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.
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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.
        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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        Decisions about HBase and Vitess
        StackShare Editors
        StackShare Editors
        Vitess
        Vitess
        MySQL
        MySQL

        They're critical to the business data and operated by an ecosystem of tools. But once the tools have been used, it was important to verify that the data remains as expected at all times. Even with the best efforts to prevent errors, inconsistencies are bound to creep at any stage. In order to test the code in a comprehensive manner, Slack developed a structure known as a consistency check framework.

        This is a responsive and personalized framework that can meaningfully analyze and report on your data with a number of proactive and reactive benefits. This framework is important because it can help with repair and recovery from an outage or bug, it can help ensure effective data migration through scripts that test the code post-migration, and find bugs throughout the database. This framework helped prevent duplication and identifies the canonical code in each case, running as reusable code.

        The framework was created by creating generic versions of the scanning and reporting code and an interface for the checking code. The checks could be run from the command line and either a single team could be scanned or the whole system. The process was improved over time to further customize the checks and make them more specific. In order to make this framework accessible to everyone, a GUI was added and connected to the internal administrative system. The framework was also modified to include code that can fix certain problems, while others are left for manual intervention. For Slack, such a tool proved extremely beneficial in ensuring data integrity both internally and externally.

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        How developers use HBase and Vitess
        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

        How much does HBase cost?
        How much does Vitess cost?
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