DBMS > Amazon Neptune vs. Bangdb vs. Microsoft Azure Table Storage vs. MySQL vs. Postgres-XL

System Properties Comparison Amazon Neptune vs. Bangdb vs. Microsoft Azure Table Storage vs. MySQL vs. Postgres-XL

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

aws.amazon.com/neptune

bangdb.com

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

www.postgres-xl.org

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.bangdb.com

dev.mysql.com/doc

www.postgres-xl.org/documentation

Developer

Amazon

Sachin Sinha, BangDB

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2012

1995

2014

since 2012, originally named StormDB

Current release

BangDB 2.0, October 2021

8.4.0, April 2024

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Mozilla public license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++

C and C++

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python

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

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

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

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

optimistic locking

ACID

not for MyISAM storage engine

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes (enterprise version only)

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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