DBMS > Bangdb vs. Infobright vs. LevelDB vs. RDF4J vs. Sequoiadb

System Properties Comparison Bangdb vs. Infobright vs. LevelDB vs. RDF4J vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store

RDF store

Document store
Relational DBMS

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	0.96
Rank	#194	Overall
	#91	Relational DBMS

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

bangdb.com

ignitetech.com/softwarelibrary/infobrightdb

github.com/google/leveldb

rdf4j.org

www.sequoiadb.com

Technical documentation

docs.bangdb.com

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

rdf4j.org/documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Sachin Sinha, BangDB

Ignite Technologies Inc.; formerly InfoBright Inc.

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Sequoiadb Ltd.

Initial release

2012

2005

2011

2004

2013

Current release

BangDB 2.0, October 2021

1.23, February 2021

License

Commercial or Open Source

Open Source

BSD 3

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Server: AGPL; Client: Apache V2

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++

C++

Java

C++

Server operating systems

Linux

Linux
Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

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

yes

oid, date, timestamp, binary, regex

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

SQL like support with command line tool

yes

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol using JSON

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

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

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

none

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Isolation support depends on the API used

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

with automatic compression on writes

yes

in-memory storage is supported 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)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

simple password-based access control

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