DBMS > Couchbase vs. ITTIA vs. LMDB vs. Oracle Rdb vs. PouchDB

System Properties Comparison Couchbase vs. ITTIA vs. LMDB vs. Oracle Rdb vs. PouchDB

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

Edge Time Series DBMS with Real-Time Stream Processing

A high performant, light-weight, embedded key-value database library

JavaScript DBMS with an API inspired by CouchDB

Primary database model

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

Relational DBMS

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.couchbase.com

www.ittia.com

www.symas.com/symas-embedded-database-lmdb

www.oracle.com/database/technologies/related/rdb.html

pouchdb.com

Technical documentation

docs.couchbase.com

www.lmdb.tech/doc

www.oracle.com/database/technologies/related/rdb-doc.html

pouchdb.com/guides

Developer

Couchbase, Inc.

ITTIA L.L.C.

Symas

Oracle, originally developed by Digital Equipment Corporation (DEC)

Apache Software Foundation

Initial release

2011

2007

2011

1984

2012

Current release

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

8.7

0.9.32, January 2024

7.4.1.1, 2021

7.1.1, June 2019

License

Commercial or Open Source

Open Source

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

commercial

Open Source

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

C, C++, Go and Erlang

C and C++

JavaScript

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
Unix
Windows

HP Open VMS

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

Data scheme

schema-free

Fixed schema

schema-free

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

via views

SQL

Support of SQL

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

yes

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

JDBC
ODBC
RESTful HTTP API
WebSocket

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C++
JavaScript (Node.js)
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

yes

none

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
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

yes

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

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.

Database file passwords

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.