DBMS > Couchbase vs. Solr vs. Trafodion

System Properties Comparison Couchbase vs. Solr vs. Trafodion

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with a powerful search engine and in-built operational and analytical capabilities

A widely used distributed, scalable search engine based on Apache Lucene

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Search engine

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

Spatial DBMS

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

Score	28.38
Rank	#30	Overall
	#5	Document stores

Score	57.26
Rank	#20	Overall
	#3	Search engines

Score	0.43
Rank	#252	Overall
	#119	Relational DBMS

Website

www.couchbase.com

lucene.apache.org/solr

trafodion.apache.org

Technical documentation

docs.couchbase.com

lucene.apache.org/solr/resources.html

trafodion.apache.org

Developer

Couchbase, Inc.

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2011

2006

2014

Current release

Server: 7.0, July 2021; Mobile: 3, February 2022; Couchbase Capella, October 2021

8.11.1, December 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

Open Source

Apache Version 2

Open Source

Apache 2.0

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.

Couchbase Capella: a fully managed database-as-a-service that eliminates database management efforts and reduces cost

Implementation language

C, C++, Go and Erlang

Java

C++, Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

String, Boolean, Number

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Declarative query language (N1QL) that extends ANSI SQL to JSON. First commercial implementation of SQL++.

Solr Parallel SQL Interface

yes

APIs and other access methods

Native language bindings for CRUD, Query, Search and Analytics APIs

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Scala

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Functions and timers in JavaScript

Java plugins

Java Stored Procedures

Triggers

yes

via the TAP protocol

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Developed as an alternative to traditionally inflexible relational databases, Couchbase...
» more

Competitive advantages

Couchbase was architected with several differentiated capabilities: Shared-nothing,...
» more

Typical application scenarios

Customer 360 for user profile, session store and data aggregation (Comcast, Equifax,...
» more

Key customers

Amadeus, AT&T, BD (Becton, Dickinson and Company), Carrefour, Cisco, Comcast, Disney,...
» more

Market metrics

Named a leader in the Forrester Wave™: Big Data NoSQL, Q1 2019 Over 10M downloads...
» more

Licensing and pricing models

The Community Edition (CE) of Couchbase Server and Couchbase Mobile are available...
» more

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