DBMS > Badger vs. EsgynDB vs. OpenQM vs. TerminusDB vs. Warp 10

System Properties Comparison Badger vs. EsgynDB vs. OpenQM vs. TerminusDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Document store
RDF store

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

github.com/dgraph-io/badger

www.esgyn.cn

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

terminusdb.com

www.warp10.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

terminusdb.github.io/terminusdb/#

www.warp10.io/content/02_Getting_started

Developer

DGraph Labs

Esgyn

Rocket Software, originally Martin Phillips

DataChemist Ltd.

SenX

Initial release

2017

2015

1993

2018

2015

Current release

3.4-12

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

Open Source

Apache License 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

Prolog, Rust

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Graph Partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

yes

Journaling Streams

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

based on HBase

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

in-memory journaling

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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