DBMS > DolphinDB vs. GBase vs. HugeGraph vs. InfluxDB vs. SiteWhere

System Properties Comparison DolphinDB vs. GBase vs. HugeGraph vs. InfluxDB vs. SiteWhere

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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A fast-speed and highly-scalable Graph DBMS

DBMS for storing time series, events and metrics

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

with GEO package

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

www.dolphindb.com

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

www.influxdata.com/products/influxdb-overview

github.com/sitewhere/sitewhere

Technical documentation

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

hugegraph.apache.org/docs

docs.influxdata.com/influxdb

sitewhere1.sitewhere.io/index.html

Developer

DolphinDB, Inc

General Data Technology Co., Ltd.

Baidu

SiteWhere

Initial release

2018

2004

2018

2013

2010

Current release

v2.00.4, January 2022

GBase 8a, GBase 8s, GBase 8c

0.9

2.7.6, April 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

Common Public Attribution License Version 1.0

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++

C, Java, Python

Java

Server operating systems

Linux
Windows

Linux

Linux
macOS
Unix

Linux
OS X

through Homebrew

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

also supports composite index and range index

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

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

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API
JSON over UDP

HTTP REST

Supported programming languages

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

Groovy
Java
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

user defined functions

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

in enterprise version only

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

in enterprise version only

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

Depending on used storage engine

User concepts

Access control

Administrators, Users, Groups

yes

Users, roles and permissions

simple rights management via user accounts

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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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.

Related products and services

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

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