DBMS > Dgraph vs. EsgynDB vs. Machbase Neo vs. Quasardb vs. Tkrzw

System Properties Comparison Dgraph vs. EsgynDB vs. Machbase Neo vs. Quasardb vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

TimeSeries DBMS for AIoT and BigData

Distributed, high-performance timeseries database

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

Technical documentation

dgraph.io/docs

machbase.com/dbms

doc.quasar.ai/master

Developer

Dgraph Labs, Inc.

Esgyn

Machbase

quasardb

Mikio Hirabayashi

Initial release

2016

2015

2013

2009

2020

Current release

V8.0, August 2023

3.14.1, January 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache Version 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++, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Windows

BSD
Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

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

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

selectable replication factor

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

volatile and lookup table

yes

Transient mode

yes

using specific database classes

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

simple password-based access control

Cryptographically strong user authentication and audit trail

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More resources

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