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

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

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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.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

Document store

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

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

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

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

github.com/dgraph-io/badger

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

www.transwarp.cn/en/product/kundb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

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

www.xtdb.com/docs

Developer

DGraph Labs

Oracle

Transwarp

Juxt Ltd.

Initial release

2017

2011

2019

Current release

24.1, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

commercial

Open Source

MIT License

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

Clojure

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

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

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes, each node contains all data

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights for users and roles

yes

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