DBMS > Couchbase vs. HugeGraph vs. JanusGraph vs. MongoDB vs. SingleStore

System Properties Comparison Couchbase vs. HugeGraph vs. JanusGraph vs. MongoDB vs. SingleStore

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 fast-speed and highly-scalable Graph DBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

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
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

www.couchbase.com

github.com/hugegraph
hugegraph.apache.org

janusgraph.org

www.mongodb.com

www.singlestore.com

Technical documentation

docs.couchbase.com

hugegraph.apache.org/docs

docs.janusgraph.org

www.mongodb.com/docs/manual

docs.singlestore.com

Developer

Couchbase, Inc.

Baidu

Linux Foundation; originally developed as Titan by Aurelius

MongoDB, Inc

SingleStore Inc.

Initial release

2011

2018

2017

2009

2013

Current release

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

0.9

0.6.3, February 2023

6.0.7, June 2023

8.5, January 2024

License

Commercial or Open Source

Open Source

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

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

commercial

free developer edition available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C, C++, Go and Erlang

Java

C++

C++, Go

Server operating systems

Linux
OS X
Windows

Linux
macOS
Unix

Linux
OS X
Unix
Windows

Linux
OS X
Solaris
Windows

Linux

64 bit version required

Data scheme

schema-free

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

also supports composite index and range index

yes

SQL

Support of SQL

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

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

but no triggers and foreign keys

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Groovy
Java
Python

Clojure
Java
Python

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

asynchronous Gremlin script jobs

yes

JavaScript

yes

Triggers

yes

via the TAP protocol

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

yes

via Faunus, a graph analytics engine

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

optional, enabled by default

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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 storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

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

Users, roles and permissions

User authentification and security via Rexster Graph Server

Access rights for users and roles

Fine grained access control via users, groups and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Customers in various industries worldwide including US and International Industry...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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F ree Tier and Enterprise Edition
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.