DBMS > Blueflood vs. Couchbase vs. eXtremeDB vs. PouchDB

System Properties Comparison Blueflood vs. Couchbase vs. eXtremeDB vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Time Series DBMS

Document store

Relational DBMS
Time Series 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

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.couchbase.com

www.mcobject.com/docs/extremedb.htm

pouchdb.com/guides

Developer

Rackspace

Couchbase, Inc.

McObject

Apache Software Foundation

Initial release

2013

2011

2001

2012

Current release

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

8.2, 2021

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

commercial

Open Source

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

Java

C, C++, Go and Erlang

C and C++

JavaScript

Server operating systems

Linux
OS X

Linux
OS X
Windows

AIX
HP-UX
Linux
macOS
Solaris
Windows

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

Data scheme

predefined scheme

schema-free

yes

schema-free

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.

support of XML interfaces available

Secondary indexes

yes

via views

SQL

Support of SQL

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

yes

with the option: eXtremeSQL

APIs and other access methods

HTTP REST

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

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Java
Lua
Python
Scala

JavaScript

Server-side scripts

Stored procedures

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

yes

View functions in JavaScript

Triggers

yes

via the TAP protocol

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Automatic Sharding

horizontal partitioning / sharding

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

including cross data center replication
Source-replica replication

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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. Role-base access control.

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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