DBMS > Amazon Neptune vs. Bangdb vs. Fauna vs. Linter

System Properties Comparison Amazon Neptune vs. Bangdb vs. Fauna vs. Linter

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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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

RDBMS for high security requirements

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

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	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Website

aws.amazon.com/neptune

bangdb.com

fauna.com

linter.ru

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.bangdb.com

docs.fauna.com

Developer

Amazon

Sachin Sinha, BangDB

Fauna, Inc.

relex.ru

Initial release

2017

2012

2014

1990

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

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++

Scala

C and C++

Server operating systems

hosted

Linux

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

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
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/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

horizontal partitioning

consistent hashing

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)

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

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

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)

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

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