DBMS > Badger vs. Derby vs. Oracle NoSQL vs. Transwarp KunDB

System Properties Comparison Badger vs. Derby vs. Oracle NoSQL vs. Transwarp KunDB

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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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Key-value store

Relational DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

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

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

github.com/dgraph-io/badger

db.apache.org/derby

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

www.transwarp.cn/en/product/kundb

Technical documentation

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

db.apache.org/derby/manuals/index.html

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

Developer

DGraph Labs

Apache Software Foundation

Oracle

Transwarp

Initial release

2017

1997

2011

Current release

10.17.1.0, November 2023

24.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache version 2

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

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC

RESTful HTTP API

Supported programming languages

Java

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Access rights for users and roles

yes

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