DBMS > DolphinDB vs. Newts vs. OpenMLDB vs. PostGIS

System Properties Comparison DolphinDB vs. Newts vs. OpenMLDB vs. PostGIS

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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.

Time Series DBMS based on Cassandra

An open-source machine learning database that provides a feature platform for training and inference

Spatial extension of PostgreSQL

Primary database model

Time Series DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.dolphindb.com

opennms.github.io/newts

openmldb.ai

postgis.net

Technical documentation

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

github.com/OpenNMS/newts/wiki

openmldb.ai/docs/zh/main

postgis.net/documentation

Developer

DolphinDB, Inc

OpenNMS Group

4 Paradigm Inc.

Initial release

2018

2014

2020

2005

Current release

v2.00.4, January 2022

2024-2 February 2024

3.4.2, February 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

Open Source

GPL v2.0

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++

Java

C++, Java, Scala

Server operating systems

Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Fixed schema

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

HTTP REST
Java API

JDBC
SQLAlchemy

Supported programming languages

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

Java

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

horizontal partitioning

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Source-replica replication

yes

based on PostgreSQL

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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