DBMS > Amazon Neptune vs. Couchbase vs. Faircom DB vs. H2 vs. SWC-DB

System Properties Comparison Amazon Neptune vs. Couchbase vs. Faircom DB vs. H2 vs. SWC-DB

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

A high performance, scalable Wide Column DBMS

Primary database model

Graph DBMS
RDF store

Document store

Key-value store
Relational DBMS

Relational DBMS

Wide column 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

Spatial DBMS

Time Series DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

aws.amazon.com/neptune

www.couchbase.com

www.faircom.com/products/faircom-db

www.h2database.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.couchbase.com

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.h2database.com/html/main.html

Developer

Amazon

Couchbase, Inc.

FairCom Corporation

Thomas Mueller

Alex Kashirin

Initial release

2017

2011

1979

2005

2020

Current release

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

V12, November 2020

2.2.220, July 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

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

commercial

Restricted, free version available

Open Source

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

Open Source

GPL V3

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++, Go and Erlang

ANSI C, C++

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

All OS with a Java VM

Linux

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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, ANSI SQL with proprietary extensions

yes

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java

C++

Server-side scripts

Stored procedures

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

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

none

Automatic Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Multi-source replication

including cross data center replication
Source-replica replication

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

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

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

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

Yes, tunable from durable to delayed durability to in-memory

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

Fine grained access rights according to SQL-standard with additional protections for files

fine grained access rights according to SQL-standard

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