DBMS > HBase vs. PlanetScale vs. Vitess

System Properties Comparison HBase vs. PlanetScale vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

hbase.apache.org

planetscale.com

vitess.io

Technical documentation

hbase.apache.org/book.html

planetscale.com/docs

vitess.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

PlanetScale

The Linux Foundation, PlanetScale

Initial release

2008

2020

2013

Current release

2.3.4, January 2021

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

Docker
Linux
macOS

Data scheme

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Coprocessors in Java

yes

proprietary syntax

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Single row ACID (across millions of columns)

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

no user groups or roles

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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Recent citations in the news

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11 March 2024, The Register

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8 November 2023, businesswire.com

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3 October 2023, TechCrunch

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