DBMS > Amazon Neptune vs. TDengine

System Properties Comparison Amazon Neptune vs. TDengine

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

Time Series DBMS and big data platform

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	2.13
Rank	#111	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.68
Rank	#132	Overall
	#10	Time Series DBMS

Website

aws.amazon.com/neptune

github.com/taosdata/TDengine
tdengine.com

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.tdengine.com

Developer

Amazon

TDEngine, previously Taos Data

Initial release

2017

2019

Current release

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

AGPL V3, also commercial editions available

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

Server operating systems

hosted

Linux
Windows

Data scheme

schema-free

yes

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

SQL

Support of SQL

Standard SQL with extensions for time-series applications

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

Triggers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

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

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

User concepts

Access control

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

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a time-series database designed to help traditional industries overcome...
» more

Competitive advantages

High Performance at Any Scale: With its distributed scalable architecture that grows...
» more

Typical application scenarios

TDengine is purpose-built for Industry 4.0 and the Industrial IoT (IIoT) and particularly...
» more

Market metrics

TDengine has garnered over 23,000 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is free, open-source software released under the AGPLv3. TDengine Enterprise...
» more

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

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