DBMS > Amazon Neptune vs. NSDb vs. Oracle vs. Postgres-XL vs. VictoriaMetrics

System Properties Comparison Amazon Neptune vs. NSDb vs. Oracle vs. Postgres-XL vs. VictoriaMetrics

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

Widely used RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Document store
Spatial DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

aws.amazon.com/neptune

nsdb.io

www.oracle.com/database

www.postgres-xl.org

victoriametrics.com

Technical documentation

aws.amazon.com/neptune/developer-resources

nsdb.io/Architecture

docs.oracle.com/en/database

www.postgres-xl.org/documentation

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Amazon

Oracle

VictoriaMetrics

Initial release

2017

1980

2014

since 2012, originally named StormDB

2018

Current release

23c, September 2023

10 R1, October 2018

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Mozilla public license

Open Source

Apache Version 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

Java, Scala

C and C++

Server operating systems

hosted

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
macOS

FreeBSD
Linux
macOS
OpenBSD

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

XML type, but no XML query functionality

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

distributed, parallel query execution

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

gRPC
HTTP REST
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

horizontal partitioning

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

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

Using Apache Lucene

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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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