DBMS > Amazon Neptune vs. SurrealDB vs. Valentina Server

System Properties Comparison Amazon Neptune vs. SurrealDB vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

A fully ACID transactional, developer-friendly, multi-model DBMS

Object-relational database and reports server

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS

Relational DBMS

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.08
Rank	#176	Overall
	#30	Document stores
	#16	Graph DBMS

Score	0.23
Rank	#302	Overall
	#136	Relational DBMS

Website

aws.amazon.com/neptune

surrealdb.com

www.valentina-db.net

Technical documentation

aws.amazon.com/neptune/developer-resources

surrealdb.com/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Amazon

SurrealDB Ltd

Paradigma Software

Initial release

2017

2022

1999

Current release

v1.5.0, May 2024

5.7.5

License

Commercial or Open Source

commercial

Open Source

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

Rust

Server operating systems

hosted

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

GraphQL
RESTful HTTP API
WebSocket

ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Deno
Go
JavaScript (Node.js)
Rust

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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