DBMS > Couchbase vs. Google Cloud Spanner vs. IBM Cloudant vs. JaguarDB vs. Lovefield

System Properties Comparison Couchbase vs. Google Cloud Spanner vs. IBM Cloudant vs. JaguarDB vs. Lovefield

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 horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store

Relational DBMS

Document store

Key-value store
Vector DBMS

Relational 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	16.59
Rank	#36	Overall
	#5	Document stores

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.couchbase.com

cloud.google.com/spanner

www.ibm.com/products/cloudant

www.jaguardb.com

google.github.io/lovefield

Technical documentation

docs.couchbase.com

cloud.google.com/spanner/docs

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

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

Developer

Couchbase, Inc.

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Google

Initial release

2011

2017

2010

2015

2014

Current release

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

3.3 July 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

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

commercial

Open Source

GPL V3.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Go and Erlang

Erlang

C++

the server part. Clients available in other languages

JavaScript

Server operating systems

Linux
OS X
Windows

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

Query statements complying to ANSI 2011

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

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

View functions (Map-Reduce) in JavaScript

Triggers

yes

via the TAP protocol

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

Multi-source replication
Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

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

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.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users can be defined per database

rights management via user accounts

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