DBMS > Badger vs. Oracle Coherence vs. Oracle NoSQL vs. Transwarp ArgoDB

System Properties Comparison Badger vs. Oracle Coherence vs. Oracle NoSQL vs. Transwarp ArgoDB

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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.

Oracles in-memory data grid solution

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Search engine

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

github.com/dgraph-io/badger

www.oracle.com/java/coherence

www.oracle.com/database/nosql/technologies/nosql

www.transwarp.cn/en/product/argodb

Technical documentation

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

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

DGraph Labs

Oracle

Transwarp

Initial release

2017

2007

2011

Current release

14.1, August 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux
Solaris SPARC/x86

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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 DML and DDL statements

yes

APIs and other access methods

JCache
JPA
RESTful HTTP API

RESTful HTTP API

Supported programming languages

.Net
C++
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with selectable consistency level

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles

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