DBMS > DolphinDB vs. LokiJS vs. Microsoft SQL Server vs. Newts vs. SQLite

System Properties Comparison DolphinDB vs. LokiJS vs. Microsoft SQL Server vs. Newts vs. SQLite

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.

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

Time Series DBMS based on Cassandra

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.dolphindb.com

github.com/techfort/LokiJS

www.microsoft.com/en-us/sql-server

opennms.github.io/newts

www.sqlite.org

Technical documentation

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

techfort.github.io/LokiJS

learn.microsoft.com/en-US/sql/sql-server

github.com/OpenNMS/newts/wiki

www.sqlite.org/docs.html

Developer

DolphinDB, Inc

Microsoft

OpenNMS Group

Dwayne Richard Hipp

Initial release

2018

2014

1989

2014

2000

Current release

v2.00.4, January 2022

SQL Server 2022, November 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

JavaScript

C++

Java

Server operating systems

Linux
Windows

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

Linux
Windows

Linux
OS X
Windows

server-less

Data scheme

yes

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST
Java API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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