DBMS > Apache Doris vs. Badger vs. Bangdb vs. SWC-DB

System Properties Comparison Apache Doris vs. Badger vs. Bangdb vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Converged and high performance database for device data, events, time series, document and graph

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Time Series DBMS

Wide column store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

doris.apache.org
github.com/apache/doris

github.com/dgraph-io/badger

bangdb.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

github.com/apache/doris/wiki

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

docs.bangdb.com

Developer

Apache Software Foundation, originally contributed from Baidu

DGraph Labs

Sachin Sinha, BangDB

Alex Kashirin

Initial release

2017

2012

2020

Current release

1.2.2, February 2023

BangDB 2.0, October 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

BSD 3

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C, C++

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

yes

SQL like support with command line tool

SQL-like query language

APIs and other access methods

JDBC
MySQL client

Proprietary protocol
RESTful HTTP API

Proprietary protocol
Thrift

Supported programming languages

Java

C
C#
C++
Java
Python

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor, Knob for CAP (enterprise version only)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

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More resources

Recent citations in the news

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1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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