DBMS > Badger vs. DolphinDB vs. Linter vs. PostGIS

System Properties Comparison Badger vs. DolphinDB vs. Linter vs. PostGIS

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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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

RDBMS for high security requirements

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

Relational DBMS

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Score	23.90
Rank	#29	Overall
	#1	Spatial DBMS

Website

github.com/dgraph-io/badger

www.dolphindb.com

linter.ru

postgis.net

Technical documentation

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

docs.dolphindb.cn/en/help200/index.html

postgis.net/documentation

Developer

DGraph Labs

DolphinDB, Inc

relex.ru

Initial release

2017

2018

1990

2005

Current release

v2.00.4, January 2022

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free community version available

commercial

Open Source

GPL v2.0

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

C++

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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