DBMS > Amazon Neptune vs. Cloudflare Workers KV vs. mSQL vs. SQLite vs. Trafodion

System Properties Comparison Amazon Neptune vs. Cloudflare Workers KV vs. mSQL vs. SQLite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, reliable graph database built for the cloud

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Graph DBMS
RDF store

Key-value store

Relational 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	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/neptune

www.cloudflare.com/developer-platform/workers-kv

hughestech.com.au/products/msql

www.sqlite.org

trafodion.apache.org

Technical documentation

aws.amazon.com/neptune/developer-resources

developers.cloudflare.com/kv/api

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

Amazon

Cloudflare

Hughes Technologies

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

2017

2018

1994

2000

2014

Current release

4.4, October 2021

3.45.3 (15 April 2024), April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

free licenses can be provided

Open Source

Public Domain

Open Source

Apache 2.0

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++, Java

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

server-less

Linux

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-92 is not fully supported

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

HTTP REST
Proprietary protocol

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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.

yes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

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

via file-system locks

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)

fine grained access rights according to SQL-standard

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