DBMS > Amazon Neptune vs. NSDb vs. Oracle Rdb vs. TimesTen

System Properties Comparison Amazon Neptune vs. NSDb vs. Oracle Rdb vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

aws.amazon.com/neptune

nsdb.io

www.oracle.com/database/technologies/related/rdb.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

aws.amazon.com/neptune/developer-resources

nsdb.io/Architecture

www.oracle.com/database/technologies/related/rdb-doc.html

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Amazon

Oracle, originally developed by Digital Equipment Corporation (DEC)

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

1984

1998

Current release

7.4.1.1, 2021

Release 22.1

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

hosted

Linux
macOS

HP Open VMS

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

gRPC
HTTP REST
WebSocket

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java
Scala

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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.

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

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

Using Apache Lucene

yes

by means of logfiles and checkpoints

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How Amazon stores deliver trustworthy shopping and seller experiences using Amazon Neptune
18 September 2024, AWS Blog

Hydrating the Natural History Museum’s Planetary Knowledge Base with Amazon Neptune and Open Data on AWS
13 September 2024, AWS Blog

How Prisma Cloud built Infinity Graph using Amazon Neptune and Amazon OpenSearch Service
27 August 2024, AWS Blog

Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune
1 August 2024, AWS Blog

New Amazon Neptune engine version delivers up to 9 times faster and 10 times higher throughput for openCypher query performance
23 July 2024, AWS Blog

provided by Google News

Oracle Adds New AI-Enabling Features To MySQL HeatWave
23 March 2023, Forbes

Oracle Business Model
13 June 2023, Business Model Analyst

2013 Data Science Salary Survey
4 May 2013, O'Reilly Media

provided by Google News

Oracle starts peddling Exalytics in-memory appliance
12 March 2012, The Register

SAP S&D Benchmark - The Intel Xeon E7-8800 v3 Review: The POWER8 Killer?
8 May 2015, AnandTech

provided by Google News

Share this page