DBMS > Cubrid vs. DolphinDB vs. Google Cloud Bigtable vs. Graph Engine vs. TDengine

System Properties Comparison Cubrid vs. DolphinDB vs. Google Cloud Bigtable vs. Graph Engine vs. TDengine

Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Key-value store
Wide column store

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.56
Rank	#241	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.48
Rank	#107	Overall
	#9	Time Series DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.dolphindb.com

cloud.google.com/bigtable

www.graphengine.io

github.com/taosdata/TDengine
tdengine.com

Technical documentation

cubrid.org/manuals

docs.dolphindb.cn/en/help200/index.html

cloud.google.com/bigtable/docs

www.graphengine.io/docs/manual

docs.tdengine.com

Developer

CUBRID Corporation, CUBRID Foundation

DolphinDB, Inc

Google

Microsoft

TDEngine, previously Taos Data

Initial release

2008

2018

2015

2010

2019

Current release

11.0, January 2021

v2.00.4, January 2022

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

commercial

Open Source

MIT License

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

C, C++, Java

C++

.NET and C

Server operating systems

Linux
Windows

hosted

.NET

Linux
Windows

Data scheme

yes

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

yes

SQL

Support of SQL

yes

SQL-like query language

Standard SQL with extensions for time-series applications

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API

JDBC
RESTful HTTP API

Supported programming languages

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

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

C#
C++
F#
Visual Basic

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

Access rights for users, groups and roles based on Google Cloud 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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