DBMS > Amazon Neptune vs. Bangdb vs. NSDb vs. NuoDB vs. SwayDB

System Properties Comparison Amazon Neptune vs. Bangdb vs. NSDb vs. NuoDB vs. SwayDB

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

NuoDB is a webscale distributed database that supports SQL and ACID transactions

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

aws.amazon.com/neptune

bangdb.com

nsdb.io

www.3ds.com/nuodb-distributed-sql-database

swaydb.simer.au

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.bangdb.com

nsdb.io/Architecture

doc.nuodb.com

Developer

Amazon

Sachin Sinha, BangDB

Dassault Systèmes

originally NuoDB, Inc.

Simer Plaha

Initial release

2017

2012

2017

2013

2018

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Java, Scala

C++

Scala

Server operating systems

hosted

Linux

Linux
macOS

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Proprietary protocol
RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python

Java
Scala

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

Java, SQL

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

data is dynamically stored/cached on the nodes where it is read/written

none

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

Managed transparently by NuoDB

none

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

Eventual Consistency

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

tunable commit protocol

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

MVCC

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes, implements WAL (Write ahead log) as well

Using Apache Lucene

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

Temporary table

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)

Standard SQL roles/ privileges, Administrative Users

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More resources

DB-Engines blog posts

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