DBMS > Amazon DynamoDB vs. QuestDB vs. TDengine vs. Ultipa

System Properties Comparison Amazon DynamoDB vs. QuestDB vs. TDengine vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

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

A high performance open source SQL database for time series data

Time Series DBMS and big data platform

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Document store
Key-value store

Time Series DBMS

Graph DBMS

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	2.70
Rank	#105	Overall
	#8	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

aws.amazon.com/dynamodb

questdb.io

github.com/taosdata/TDengine
tdengine.com

www.ultipa.com

Technical documentation

docs.aws.amazon.com/dynamodb

questdb.io/docs

docs.tdengine.com

www.ultipa.com/document

Developer

Amazon

QuestDB Technology Inc

TDEngine, previously Taos Data

Ultipa

Initial release

2012

2014

2019

Current release

3.0, August 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

Open Source

AGPL V3, also commercial editions 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

Java (Zero-GC), C++, Rust

Server operating systems

hosted

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free via InfluxDB Line Protocol

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

yes

SQL

Support of SQL

SQL with time-series extensions

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP API

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by timestamps)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with eventual consistency

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

ACID for single-table writes

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

through memory mapped files

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

Relational model with native time series support Column-based storage and time partitioned...
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TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
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Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Market metrics

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

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

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

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