DBMS > Dgraph vs. EJDB vs. EsgynDB vs. HarperDB vs. OrigoDB

System Properties Comparison Dgraph vs. EJDB vs. EsgynDB vs. HarperDB vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A fully ACID in-memory object graph database

Primary database model

Document store
Object oriented DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

dgraph.io

github.com/Softmotions/ejdb

www.esgyn.cn

www.harperdb.io

origodb.com

Technical documentation

dgraph.io/docs

github.com/Softmotions/ejdb/blob/master/README.md

docs.harperdb.io/docs

origodb.com/docs

Developer

Dgraph Labs, Inc.

Softmotions

Esgyn

HarperDB

Robert Friberg et al

Initial release

2016

2012

2015

2017

2009

under the name LiveDB

Current release

3.1, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

commercial

free community edition available

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++, Java

Node.js

Server operating systems

Linux
OS X
Windows

server-less

Linux

Linux
OS X

Linux
Windows

Data scheme

schema-free

yes

dynamic schema

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

JSON data types

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like data manipulation statements

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

in-process shared library

ADO.NET
JDBC
ODBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

A table resides as a whole on one (or more) nodes in a cluster

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

none

Multi-source replication between multi datacenters

yes

the nodes on which a table resides can be defined

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

depending on model

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Access rights for users and roles

Role based authorization

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More resources

Recent citations in the news

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

Dgraph raises $3M for its open-source distributed graph database, hits 1.0 release
19 December 2017, TechCrunch

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provided by Google News

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