DBMS > Couchbase vs. Drizzle vs. Kyligence Enterprise vs. Realm

System Properties Comparison Couchbase vs. Drizzle vs. Kyligence Enterprise vs. Realm

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A distributed analytics engine for big data, built on top of Apache Kylin

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Document store

Relational DBMS

Document store

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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

www.couchbase.com

kyligence.io/kyligence-enterprise

realm.io

Technical documentation

docs.couchbase.com

realm.io/docs

Developer

Couchbase, Inc.

Drizzle project, originally started by Brian Aker

Kyligence, Inc.

Realm, acquired by MongoDB in May 2019

Initial release

2011

2008

2016

2014

Current release

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

7.2.4, September 2012

License

Commercial or Open Source

Open Source

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

Open Source

GNU GPL

commercial

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C, C++, Go and Erlang

C++

Java

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux

Android
Backend: server-less
iOS
Windows

Data scheme

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

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

yes

with proprietary extensions

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

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

JDBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
Java
PHP

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

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

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via the TAP protocol

hooks for callbacks inside the server can be used.

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

In-Memory realm

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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