DBMS > Amazon DynamoDB vs. Microsoft Azure Table Storage vs. OpenQM vs. Realm vs. TDengine

System Properties Comparison Amazon DynamoDB vs. Microsoft Azure Table Storage vs. OpenQM vs. Realm vs. TDengine

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

A Wide Column Store for rapid development using massive semi-structured datasets

QpenQM is a high-performance, self-tuning, multi-value DBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Time Series DBMS and big data platform

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Website

aws.amazon.com/dynamodb

azure.microsoft.com/en-us/services/storage/tables

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

realm.io

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.aws.amazon.com/dynamodb

realm.io/docs

docs.tdengine.com

Developer

Amazon

Microsoft

Rocket Software, originally Martin Phillips

Realm, acquired by MongoDB in May 2019

TDEngine, previously Taos Data

Initial release

2012

1993

2014

2019

Current release

3.4-12

3.0, August 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

GPLv2, extended commercial license available

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

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Linux
Windows

Data scheme

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

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

Server-side scripts

Stored procedures

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

by integration with AWS Lambda

yes

Change Listeners

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

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

Access rights based on private key authentication or shared access signatures

Access rights can be defined down to the item level

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
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Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Comprehensive Comparison Between TDengine and MongoDB
6 June 2024

Comprehensive Comparison Between TDengine and TimescaleDB
5 June 2024

Mastering Memory Leak Detection in TDengine
31 May 2024

Seamless Data Integration from MQTT and InfluxDB to TDengine
22 May 2024

Solving Long Query Performance Bottlenecks
22 May 2024

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