DBMS > DolphinDB vs. GBase vs. Ignite vs. Kingbase vs. Newts

System Properties Comparison DolphinDB vs. GBase vs. Ignite vs. Kingbase vs. Newts

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.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Time Series DBMS based on Cassandra

Primary database model

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Document store
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	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

opennms.github.io/newts

Technical documentation

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

apacheignite.readme.io/docs

github.com/OpenNMS/newts/wiki

Developer

DolphinDB, Inc

General Data Technology Co., Ltd.

Apache Software Foundation

BeiJing KINGBASE Information technologies inc.

OpenNMS Group

Initial release

2018

2004

2015

1999

2014

Current release

v2.00.4, January 2022

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

V8.0, August 2021

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

commercial

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++

C, Java, Python

C++, Java, .Net

C and Java

Java

Server operating systems

Linux
Windows

Linux

Linux
OS X
Solaris
Windows

Linux
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Standard with numerous extensions

ANSI-99 for query and DML statements, subset of DDL

Standard with numerous extensions

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP REST
Java API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Sharding

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

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

yes

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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