DBMS > Altibase vs. Couchbase vs. H2 vs. PlanetScale

System Properties Comparison Altibase vs. Couchbase vs. H2 vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Spatial DBMS

Document store
Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.couchbase.com

www.h2database.com/html/main.html

planetscale.com/docs

Developer

Altibase

Couchbase, Inc.

Thomas Mueller

PlanetScale

Initial release

1999

2011

2005

2020

Current release

v7.3, 2023, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

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

C++

C, C++, Go and Erlang

Java

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Windows

All OS with a Java VM

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

ANSI SQL-92

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
C++
Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java

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

stored procedures and stored functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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