DBMS > DolphinDB vs. EsgynDB vs. Galaxybase vs. Hive

System Properties Comparison DolphinDB vs. EsgynDB vs. Galaxybase vs. Hive

Please select another system to include it in the comparison.

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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Scalable, ACID-compliant native distributed parallel graph platform

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Primary database model

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

Technical documentation

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

cwiki.apache.org/confluence/display/Hive/Home

Developer

DolphinDB, Inc

Esgyn

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

Apache Software Foundation

initially developed by Facebook

Initial release

2018

2015

2017

2012

Current release

v2.00.4, January 2022

Nov 20, November 2021

3.1.3, April 2022

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache Version 2

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

C and Java

Java

Server operating systems

Linux
Windows

Linux

All OS with a Java VM

Data scheme

yes

Strong typed 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

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

ADO.NET
JDBC
ODBC

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

JDBC
ODBC
Thrift

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
Python

C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined procedures and functions

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Role-based access control

Access rights for users, groups and roles

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Apache Software Foundation Announces Apache® Hive 4.0
30 April 2024, GlobeNewswire

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

DataCentral: Uber's Observability and Chargeback Platform
1 February 2024, Uber

provided by Google News

Share this page