DBMS > Couchbase vs. Lovefield vs. RavenDB vs. XTDB

System Properties Comparison Couchbase vs. Lovefield vs. RavenDB vs. XTDB

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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

Embeddable relational database for web apps written in pure JavaScript

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Document store

Relational DBMS

Document 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

Graph DBMS
Spatial 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.couchbase.com

google.github.io/lovefield

ravendb.net

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

Technical documentation

docs.couchbase.com

github.com/google/lovefield/blob/master/docs/spec_index.md

ravendb.net/docs

www.xtdb.com/docs

Developer

Couchbase, Inc.

Google

Hibernating Rhinos

Juxt Ltd.

Initial release

2011

2014

2010

2019

Current release

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

2.1.12, February 2017

5.4, July 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

Open Source

MIT License

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

JavaScript

Clojure

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
macOS
Raspberry Pi
Windows

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

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language (RQL)

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
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

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

yes

Triggers

yes

via the TAP protocol

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

Multi-source replication

yes, each node contains all data

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

using MemoryDB

User concepts

Access control

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

Authorization levels configured per client per database

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