DBMS > Dgraph vs. EsgynDB vs. JSqlDb vs. Netezza vs. Quasardb

System Properties Comparison Dgraph vs. EsgynDB vs. JSqlDb vs. Netezza vs. Quasardb

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Distributed and scalable native Graph DBMS

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

JavaScript Query Language Database, stores JavaScript objects and primitives

Data warehouse and analytics appliance part of IBM PureSystems

Distributed, high-performance timeseries database

Primary database model

Graph DBMS

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

Time Series DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

dgraph.io

www.esgyn.cn

jsqldb.org (offline)

www.ibm.com/products/netezza

quasar.ai

Technical documentation

dgraph.io/docs

doc.quasar.ai/master

Developer

Dgraph Labs, Inc.

Esgyn

Konrad von Backstrom

IBM

quasardb

Initial release

2016

2015

2018

2000

2009

Current release

0.8, December 2018

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

commercial

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

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

Linux

included in appliance

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

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

JDBC
ODBC
OLE DB

HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

Java Stored Procedures

functions in JavaScript

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

none

Source-replica replication

Source-replica replication with selectable replication factor

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

using RocksDB

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Cryptographically strong user authentication and audit trail

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More resources

Recent citations in the news

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