DBMS > Amazon Neptune vs. GreptimeDB vs. Sadas Engine vs. SiteWhere

System Properties Comparison Amazon Neptune vs. GreptimeDB vs. Sadas Engine vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

M2M integration platform for persisting/querying time series data

Primary database model

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	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

aws.amazon.com/neptune

greptime.com

www.sadasengine.com

github.com/sitewhere/sitewhere

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.greptime.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

sitewhere1.sitewhere.io/index.html

Developer

Amazon

Greptime Inc.

SADAS s.r.l.

SiteWhere

Initial release

2017

2022

2006

2010

Current release

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version available

Open Source

Common Public Attribution License Version 1.0

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

Rust

C++

Java

Server operating systems

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free, schema definition possible

yes

predefined scheme

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

gRPC
HTTP API
JDBC

JDBC
ODBC
Proprietary protocol

HTTP REST

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C++
Erlang
Go
Java
JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Sharding

based on HBase

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

selectable replication factor

based on HBase

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

yes

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.

yes

managed by 'Learn by Usage'

User concepts

Access control

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

Simple rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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