DBMS > Amazon Neptune vs. DolphinDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. VelocityDB

System Properties Comparison Amazon Neptune vs. DolphinDB vs. InfluxDB vs. Microsoft Azure Cosmos DB vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS
Object oriented DBMS

Secondary database models

Relational DBMS

Spatial DBMS

with GEO package

Spatial 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	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

aws.amazon.com/neptune

www.dolphindb.com

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

velocitydb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.dolphindb.cn/en/help200/index.html

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

velocitydb.com/UserGuide

Developer

Amazon

DolphinDB, Inc

Microsoft

VelocityDB Inc

Initial release

2017

2018

2013

2014

2011

Current release

v2.00.4, January 2022

2.7.6, April 2024

7.x

License

Commercial or Open Source

commercial

free community version available

Open Source

MIT-License; commercial enterprise version available

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

C++

Server operating systems

hosted

Linux
Windows

Linux
OS X

through Homebrew

hosted

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

HTTP API
JSON over UDP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

.Net

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

JavaScript

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

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

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes

Multi-item ACID transactions with snapshot isolation within a partition

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

Depending on used storage engine

yes

User concepts

Access control

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

Administrators, Users, Groups

simple rights management via user accounts

Access rights can be defined down to the item level

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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