DBMS > Bangdb vs. BoltDB vs. mSQL vs. SQLite vs. TypeDB

System Properties Comparison Bangdb vs. BoltDB vs. mSQL vs. SQLite vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

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

An embedded key-value store for Go.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS

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

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

bangdb.com

github.com/boltdb/bolt

hughestech.com.au/products/msql

www.sqlite.org

typedb.com

Technical documentation

docs.bangdb.com

www.sqlite.org/docs.html

typedb.com/docs

Developer

Sachin Sinha, BangDB

Hughes Technologies

Dwayne Richard Hipp

Vaticle

Initial release

2012

2013

1994

2000

2016

Current release

BangDB 2.0, October 2021

4.4, October 2021

3.46.0 (23 May 2024), May 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

MIT License

commercial

free licenses can be provided

Open Source

Public Domain

Open Source

GPL Version 3, commercial licenses available

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++

Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

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

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

C
C#
C++
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

none

Immediate Consistency

Foreign keys

Referential integrity

yes

substituted by the relationship feature

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

via file-system locks

yes

Durability

Support for making data persistent

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

yes

User concepts

Access control

yes (enterprise version only)

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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