DBMS > Google BigQuery vs. MarkLogic vs. Microsoft Azure SQL Database vs. TDengine

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

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Operational and transactional Enterprise NoSQL database

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

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

cloud.google.com/bigquery

www.marklogic.com

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

github.com/taosdata/TDengine
tdengine.com

Technical documentation

cloud.google.com/bigquery/docs

docs.marklogic.com

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

docs.tdengine.com

Developer

Google

MarkLogic Corp.

Microsoft

TDEngine, previously Taos Data

Initial release

2010

2001

2010

2019

Current release

11.0, December 2022

V12

3.0, August 2022

License

Commercial or Open Source

commercial

restricted free version is available

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

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux
Windows

Data scheme

yes

schema-free

Schema can be enforced

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

yes

SQL92

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

RESTful HTTP/JSON API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

via XQuery or JavaScript

Transact SQL

Triggers

yes

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

yes

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Role-based access control at the document and subdocument levels

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...
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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...
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Licensing and pricing models

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

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