DBMS > Couchbase vs. Solr vs. Sqrrl

System Properties Comparison Couchbase vs. Solr vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

JSON-based document store derived from CouchDB with a Memcached-compatible interface

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension

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

Score	31.00
Rank	#26	Overall
	#4	Document stores

Score	50.21
Rank	#21	Overall
	#3	Search engines

Website

www.couchbase.com

lucene.apache.org/solr

sqrrl.com

Technical documentation

docs.couchbase.com

lucene.apache.org/solr/resources.html

Developer

Couchbase, Inc.

Apache Software Foundation

Amazon

originally Sqrrl Data, Inc.

Initial release

2011

2006

2012

Current release

Server: 6.5, January 2020; Mobile: 2.7, January 2020; Couchbase Autonomous Operator: 1.2, May 2019

8.8.1, February 2021

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Couchbase Cloud: Deploy, manage, and operate Couchbase in a few clicks

Implementation language

C, C++, Go and Erlang

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

schema-free

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

APIs and other access methods

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

Java API
RESTful HTTP/JSON API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
C
Clojure
ColdFusion
Erlang
Go
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala
Tcl

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

Functions and timers in JavaScript

Java plugins

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

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

Transaction concepts

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

ACID

optimistic locking

Atomic updates per row, document, or graph entity

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

Developed as an alternative to traditionally inflexible relational databases, Couchbase...
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Competitive advantages

Couchbase was architected with several differentiated capabilities: Shared-nothing,...
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Typical application scenarios

Customer 360 for user profile, session store and data aggregation (Comcast, Equifax,...
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Key customers

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

Named a leader in the Forrester Wave™: Big Data NoSQL, Q1 2019 Over 10M downloads...
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Licensing and pricing models

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