DBMS > DolphinDB vs. Galaxybase vs. Heroic vs. OpenTenBase

System Properties Comparison DolphinDB vs. Galaxybase vs. Heroic vs. OpenTenBase

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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.

Scalable, ACID-compliant native distributed parallel graph platform

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Website

www.dolphindb.com

galaxybase.com

github.com/spotify/heroic

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

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

spotify.github.io/heroic

docs.opentenbase.org
docs.opentenbase.org/en

Developer

DolphinDB, Inc

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Spotify

OpenAtom Foundation, previously Tencent

Initial release

2018

2017

2014

Current release

v2.00.4, January 2022

Nov 20, November 2021

2.5, January 2024

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

BSD-3

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 and Java

Java

Server operating systems

Linux
Windows

Linux

Data scheme

yes

Strong typed schema

schema-free

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.

Secondary indexes

yes

via Elasticsearch

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

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

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

Go
Java
Python

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined procedures and functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Role-based access control

Access rights for users, groups and roles according to SQL-standard

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