DBMS > Amazon Neptune vs. Apache Doris vs. GreptimeDB

System Properties Comparison Amazon Neptune vs. Apache Doris vs. GreptimeDB

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

An MPP-based analytics DBMS embracing the MySQL protocol

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Primary database model

Graph DBMS
RDF store

Relational DBMS

Time Series DBMS

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

Score	2.11
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.51
Rank	#244	Overall
	#115	Relational DBMS

Score	0.13
Rank	#335	Overall
	#30	Time Series DBMS

Website

aws.amazon.com/neptune

doris.apache.org
github.com/apache/doris

greptime.com

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/apache/doris/wiki

docs.greptime.com

Developer

Amazon

Apache Software Foundation, originally contributed from Baidu

Greptime Inc.

Initial release

2017

2022

Current release

1.2.2, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Rust

Server operating systems

hosted

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free, schema definition possible

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
MySQL client

gRPC
HTTP API
JDBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Java

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

user defined functions

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

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.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

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.

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

Simple rights management via user accounts

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