DBMS > Bangdb vs. Microsoft SQL Server vs. Neo4j vs. Oracle vs. Tkrzw

System Properties Comparison Bangdb vs. Microsoft SQL Server vs. Neo4j vs. Oracle vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Widely used RDBMS

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

bangdb.com

www.microsoft.com/en-us/sql-server

neo4j.com

www.oracle.com/database

dbmx.net/tkrzw

Technical documentation

docs.bangdb.com

learn.microsoft.com/en-US/sql/sql-server

neo4j.com/docs

docs.oracle.com/en/database

Developer

Sachin Sinha, BangDB

Microsoft

Neo4j, Inc.

Oracle

Mikio Hirabayashi

Initial release

2012

1989

2007

1980

2020

Current release

BangDB 2.0, October 2021

SQL Server 2022, November 2022

5.19, April 2024

23c, September 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD 3

commercial

restricted free version is available

Open Source

GPL version3, commercial licenses available

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Java, Scala

C and C++

C++

Server operating systems

Linux

Linux
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS

Data scheme

schema-free

yes

schema-free and schema-optional

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

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

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

yes

pluggable indexing subsystem, by default Apache Lucene

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

User defined Procedures and Functions

PL/SQL

also stored procedures in Java possible

Triggers

yes, Notifications (with Streaming only)

yes

via event handler

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes using Neo4j Fabric

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, but depending on the SQL-Server Edition

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

using specific database classes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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Licensing and pricing models

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