DBMS > Amazon Redshift vs. Bangdb vs. Couchbase vs. PouchDB vs. Sphinx

System Properties Comparison Amazon Redshift vs. Bangdb vs. Couchbase vs. PouchDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Converged and high performance database for device data, events, time series, document and graph

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

JavaScript DBMS with an API inspired by CouchDB

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Document store

Search engine

Secondary database models

Spatial DBMS

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	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.bangdb.com

docs.couchbase.com

pouchdb.com/guides

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Sachin Sinha, BangDB

Couchbase, Inc.

Apache Software Foundation

Sphinx Technologies Inc.

Initial release

2012

2011

2012

2001

Current release

BangDB 2.0, October 2021

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

7.1.1, June 2019

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

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

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C, C++, Go and Erlang

JavaScript

C++

Server operating systems

hosted

Linux

Linux
OS X
Windows

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

restricted

yes

secondary, composite, nested, reverse, geospatial

yes

via views

yes

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL like support with command line tool

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

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

Proprietary protocol
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HTTP REST

only for PouchDB Server
JavaScript API

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

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

View functions in JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic Sharding

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

yes, run db with in-memory only mode

yes

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

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

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