DBMS > Google BigQuery vs. H2 vs. Microsoft Azure SQL Database vs. TDengine vs. TinkerGraph

System Properties Comparison Google BigQuery vs. H2 vs. Microsoft Azure SQL Database vs. TDengine vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Database as a Service offering with high compatibility to Microsoft SQL Server

Time Series DBMS and big data platform

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	2.68
Rank	#106	Overall
	#9	Time Series DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Website

cloud.google.com/bigquery

www.h2database.com

azure.microsoft.com/en-us/products/azure-sql/database

github.com/taosdata/TDengine
tdengine.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

docs.microsoft.com/en-us/azure/azure-sql

docs.tdengine.com

Developer

Google

Thomas Mueller

Microsoft

TDEngine, previously Taos Data

Initial release

2010

2005

2010

2019

2009

Current release

2.2.220, July 2023

V12

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

AGPL V3, also commercial editions available

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

hosted

All OS with a Java VM

hosted

Linux
Windows

Data scheme

yes

schema-free

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

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API

TinkerPop 3

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

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

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

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Transact SQL

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, with always 3 replicas available

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

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

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

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

What Is Predictive Maintenance?
17 May 2024

Can Typical Time-Series Databases Replace Data Historians?
8 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.