DBMS > Bangdb vs. InfinityDB vs. LevelDB vs. MySQL

System Properties Comparison Bangdb vs. InfinityDB vs. LevelDB vs. MySQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Widely used open source RDBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

Document store
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	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

bangdb.com

boilerbay.com

github.com/google/leveldb

www.mysql.com

Technical documentation

docs.bangdb.com

boilerbay.com/infinitydb/manual

github.com/google/leveldb/blob/main/doc/index.md

dev.mysql.com/doc

Developer

Sachin Sinha, BangDB

Boiler Bay Inc.

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2012

2002

2011

1995

Current release

BangDB 2.0, October 2021

4.0

1.23, February 2021

8.4.0, April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C, C++

Java

C++

C and C++

Server operating systems

Linux

All OS with a Java VM

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

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

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

secondary, composite, nested, reverse, geospatial

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C#
C++
Java
Python

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

with automatic compression on writes

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)

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.