DBMS > AgensGraph vs. BigchainDB vs. Couchbase vs. EventStoreDB vs. eXtremeDB

System Properties Comparison AgensGraph vs. BigchainDB vs. Couchbase vs. EventStoreDB vs. eXtremeDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Natively in-memory DBMS with options for persistency, high-availability and clustering

Primary database model

Graph DBMS
Relational DBMS

Document store

Event Store

Relational 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

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Website

bitnine.net/agensgraph

Technical documentation

bitnine.net/documentation

bigchaindb.readthedocs.io/en/latest

docs.couchbase.com

developers.eventstore.com

www.mcobject.com/docs/extremedb.htm

Developer

Bitnine Global Inc.

Couchbase, Inc.

Event Store Limited

McObject

Initial release

2016

2011

2012

2001

Current release

2.1, December 2018

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

21.2, February 2021

8.2, 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

AGPL v3

Open Source

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

Open Source

commercial

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

Python

C, C++, Go and Erlang

C and C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Linux
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

Data scheme

depending on used data model

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.

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

with the option: eXtremeSQL

APIs and other access methods

Cypher Query Language
JDBC

CLI Client
RESTful HTTP API

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

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Supported programming languages

C
Java
JavaScript
Python

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Java
Lua
Python
Scala

Server-side scripts

Stored procedures

yes

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

yes

Triggers

yes

via the TAP protocol

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

Automatic Sharding

horizontal partitioning / sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Multi-source replication

including cross data center replication
Source-replica replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

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

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

Optimistic (MVCC) and pessimistic (locking) strategies available

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

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

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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