DBMS > DolphinDB vs. IBM Cloudant vs. Linter vs. LMDB vs. Lovefield

System Properties Comparison DolphinDB vs. IBM Cloudant vs. Linter vs. LMDB vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Database as a Service offering based on Apache CouchDB

RDBMS for high security requirements

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

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.dolphindb.com

www.ibm.com/products/cloudant

linter.ru

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

google.github.io/lovefield

Technical documentation

docs.dolphindb.cn/en/help200/index.html

cloud.ibm.com/docs/Cloudant

www.lmdb.tech/doc

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

DolphinDB, Inc

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

relex.ru

Symas

Google

Initial release

2018

2010

1990

2011

2014

Current release

v2.00.4, January 2022

0.9.32, January 2024

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

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++

Erlang

C and C++

JavaScript

Server operating systems

Linux
Windows

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP/JSON API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.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

yes

View functions (Map-Reduce) in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Administrators, Users, Groups

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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