DBMS > atoti vs. Badger vs. OushuDB vs. TerminusDB

System Properties Comparison atoti vs. Badger vs. OushuDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

Primary database model

Secondary database models

Document store
RDF store

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

atoti.io

github.com/dgraph-io/badger

www.oushu.com/product/oushuDB

terminusdb.com

Technical documentation

docs.atoti.io

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

www.oushu.com/documentation

terminusdb.github.io/terminusdb/#

Developer

ActiveViam

DGraph Labs

Oushu

DataChemist Ltd.

Initial release

2017

2018

Current release

4.0.1, August 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

commercial

Open Source

GPL V3

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

Java

Prolog, Rust

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

Full-featured ANSI SQL support

SQL-like query language (WOQL)

APIs and other access methods

JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++

JavaScript
Python

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

yes

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

yes

User concepts

Access control

Kerberos, SSL and role based access

Role-based access control

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