DBMS > Couchbase vs. OrigoDB vs. SWC-DB vs. XTDB vs. Yanza

System Properties Comparison Couchbase vs. OrigoDB vs. SWC-DB vs. XTDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it 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

A fully ACID in-memory object graph database

A high performance, scalable Wide Column DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Time Series DBMS for IoT Applications

Primary database model

Document store

Document store
Object oriented DBMS

Wide column store

Document store

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

Time Series DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.couchbase.com

origodb.com

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

github.com/xtdb/xtdb
www.xtdb.com

yanza.com

Technical documentation

docs.couchbase.com

origodb.com/docs

www.xtdb.com/docs

Developer

Couchbase, Inc.

Robert Friberg et al

Alex Kashirin

Juxt Ltd.

Yanza

Initial release

2011

2009

under the name LiveDB

2020

2019

2015

Current release

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

0.5, April 2021

1.19, September 2021

License

Commercial or Open Source

Open Source

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

Open Source

GPL V3

Open Source

MIT License

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++

Clojure

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes, extensible-data-notation format

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

limited SQL, making use of 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

.NET Client API
HTTP API
LINQ

Proprietary protocol
Thrift

HTTP REST
JDBC

HTTP API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net

C++

Clojure
Java

any language that supports HTTP calls

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via the TAP protocol

yes

Domain Events

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

yes, each node contains all data

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

depending on model

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

Write ahead log

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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

Role based authorization

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