DBMS > Altibase vs. Google Cloud Firestore vs. Microsoft SQL Server vs. SpaceTime vs. TDengine

System Properties Comparison Altibase vs. Google Cloud Firestore vs. Microsoft SQL Server vs. SpaceTime vs. TDengine

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Microsofts flagship relational DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Time Series DBMS and big data platform

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

altibase.com

firebase.google.com/products/firestore

www.microsoft.com/en-us/sql-server

www.mireo.com/spacetime

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

firebase.google.com/docs/firestore

learn.microsoft.com/en-US/sql/sql-server

docs.tdengine.com

Developer

Altibase

Google

Microsoft

Mireo

TDEngine, previously Taos Data

Initial release

1999

2017

1989

2020

2019

Current release

v7.3, 2023, August 2023

SQL Server 2022, November 2022

3.0, August 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

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

AIX
HP-UX
Linux

hosted

Linux
Windows

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

yes

A subset of ANSI SQL is implemented

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

RESTful HTTP API

JDBC
RESTful HTTP API

Supported programming languages

C
C++
Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
C++
Python

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

Server-side scripts

Stored procedures

stored procedures and stored functions

yes, Firebase Rules & Cloud Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

yes, with Cloud Functions

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

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

ACID

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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

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

TDengine 3.3.0.0 Release Notes
7 May 2024

How to Unlock Value from Industrial Data with AI and ML Technology
6 May 2024

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 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.