DBMS > Couchbase vs. Realm vs. TerminusDB vs. VictoriaMetrics

System Properties Comparison Couchbase vs. Realm vs. TerminusDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines

Name

Description

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

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Document store

Graph DBMS

Time Series 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

Document store
RDF store

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	1.32
Rank	#162	Overall
	#14	Time Series DBMS

Website

Technical documentation

docs.couchbase.com

realm.io/docs

terminusdb.github.io/terminusdb/#

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Couchbase, Inc.

Realm, acquired by MongoDB in May 2019

DataChemist Ltd.

VictoriaMetrics

Initial release

2011

2014

2018

Current release

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

11.0.0, January 2023

v1.91, May 2023

License

Commercial or Open Source

Open Source

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

Open Source

GPL V3

Open Source

Apache Version 2.0

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

Prolog, Rust

Server operating systems

Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Linux

FreeBSD
Linux
macOS
OpenBSD

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

SQL-like query language (WOQL)

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript
Python

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

yes

Triggers

yes

via the TAP protocol

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

Journaling Streams

Synchronous replication

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

Eventual 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 journaling

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.

yes

Role-based access control

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