DBMS > DolphinDB vs. EsgynDB vs. JanusGraph vs. PouchDB

System Properties Comparison DolphinDB vs. EsgynDB vs. JanusGraph vs. PouchDB

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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.

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Time Series DBMS
Vector DBMS

Relational DBMS

Graph DBMS

Document store

Secondary database models

Relational DBMS

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

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

Technical documentation

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

docs.janusgraph.org

pouchdb.com/guides

Developer

DolphinDB, Inc

Esgyn

Linux Foundation; originally developed as Titan by Aurelius

Apache Software Foundation

Initial release

2018

2015

2017

2012

Current release

v2.00.4, January 2022

1.0.0, October 2023

7.1.1, June 2019

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

Apache 2.0

Open Source

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

Java

JavaScript

Server operating systems

Linux
Windows

Linux

Linux
OS X
Unix
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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

via views

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

ADO.NET
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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