DBMS > Badger vs. Lovefield vs. Oracle Coherence vs. TerminusDB

System Properties Comparison Badger vs. Lovefield vs. Oracle Coherence vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Oracles in-memory data grid solution

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	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Website

github.com/dgraph-io/badger

google.github.io/lovefield

www.oracle.com/java/coherence

terminusdb.com

Technical documentation

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

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/en/middleware/standalone/coherence

terminusdb.github.io/terminusdb/#

Developer

DGraph Labs

Google

Oracle

DataChemist Ltd.

Initial release

2017

2014

2007

2018

Current release

2.1.12, February 2017

14.1, August 2023

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

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

JavaScript

Java

Prolog, Rust

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

All OS with a Java VM

Linux

Data scheme

schema-free

yes

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language (WOQL)

APIs and other access methods

JCache
JPA
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

JavaScript

.Net
C++
Java

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

optionally

yes

in-memory journaling

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

authentification to access the cache via certificates or http basic authentication

Role-based access control

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