DBMS > Badger vs. Quasardb vs. SQLite vs. SurrealDB

System Properties Comparison Badger vs. Quasardb vs. SQLite vs. SurrealDB

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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.

Distributed, high-performance timeseries database

Widely used embeddable, in-process RDBMS

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Document store
Graph DBMS

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

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

github.com/dgraph-io/badger

quasar.ai

www.sqlite.org

surrealdb.com

Technical documentation

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

doc.quasar.ai/master

www.sqlite.org/docs.html

surrealdb.com/docs

Developer

DGraph Labs

quasardb

Dwayne Richard Hipp

SurrealDB Ltd

Initial release

2017

2009

2000

2022

Current release

3.14.1, January 2024

3.45.3 (15 April 2024), April 2024

v1.1.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Public Domain

Open Source

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++

Rust

Server operating systems

BSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

server-less

Linux
macOS
Windows

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

yes

not rigid because of 'dynamic typing' concept.

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

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication with selectable replication factor

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Cryptographically strong user authentication and audit trail

yes, based on authentication and database rules

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