DBMS > DolphinDB vs. GeoMesa vs. Graph Engine vs. Newts

System Properties Comparison DolphinDB vs. GeoMesa vs. Graph Engine vs. Newts

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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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS based on Cassandra

Primary database model

Time Series DBMS

Spatial DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	0.81
Rank	#214	Overall
	#4	Spatial DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

www.dolphindb.com

www.geomesa.org

www.graphengine.io

opennms.github.io/newts

Technical documentation

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

www.geomesa.org/documentation/stable/user/index.html

www.graphengine.io/docs/manual

github.com/OpenNMS/newts/wiki

Developer

DolphinDB, Inc

CCRi and others

Microsoft

OpenNMS Group

Initial release

2018

2014

2010

2014

Current release

v2.00.4, January 2022

4.0.5, February 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache License 2.0

Open Source

MIT License

Open Source

Apache 2.0

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++

Scala

.NET and C

Java

Server operating systems

Linux
Windows

.NET

Linux
OS X
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

HTTP REST
Java API

Supported programming languages

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

C#
C++
F#
Visual Basic

Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

depending on storage layer

horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

depending on storage layer

yes

User concepts

Access control

Administrators, Users, Groups

yes

depending on the DBMS used for storage

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More resources

DB-Engines blog posts

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6 April 2021, Matthias Gelbmann

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