DBMS > 4D vs. Amazon Neptune vs. Microsoft Azure Table Storage vs. RocksDB vs. RRDtool

System Properties Comparison 4D vs. Amazon Neptune vs. Microsoft Azure Table Storage vs. RocksDB vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Fast, reliable graph database built for the cloud

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.4d.com

aws.amazon.com/neptune

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

rocksdb.org

oss.oetiker.ch/rrdtool

Technical documentation

developer.4d.com

aws.amazon.com/neptune/developer-resources

github.com/facebook/rocksdb/wiki

oss.oetiker.ch/rrdtool/doc

Developer

4D, Inc

Amazon

Microsoft

Facebook, Inc.

Tobias Oetiker

Initial release

1984

2017

2012

2013

1999

Current release

v20, April 2023

8.11.4, April 2024

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

GPL V2 and FLOSS

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

OS X
Windows

hosted

Linux

HP-UX
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

close to SQL 92

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

RESTful HTTP API

C++ API
Java API

in-process shared library
Pipes

Supported programming languages

4D proprietary IDE
PHP

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

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

C
C++
Go
Java
Perl
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

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

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Users and groups

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

Access rights based on private key authentication or shared access signatures

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