DBMS > AlaSQL vs. GBase vs. Google Cloud Bigtable vs. ObjectBox vs. TDengine

System Properties Comparison AlaSQL vs. GBase vs. Google Cloud Bigtable vs. ObjectBox vs. TDengine

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Extremely fast embedded database for small devices, IoT and Mobile

Time Series DBMS and big data platform

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store
Wide column store

Object oriented DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

alasql.org

www.gbase.cn

cloud.google.com/bigtable

objectbox.io

github.com/taosdata/TDengine
tdengine.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigtable/docs

docs.objectbox.io

docs.tdengine.com

Developer

Andrey Gershun & Mathias R. Wulff

General Data Technology Co., Ltd.

Google

ObjectBox Limited

TDEngine, previously Taos Data

Initial release

2014

2004

2015

2017

2019

Current release

GBase 8a, GBase 8s, GBase 8c

3.0, August 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache License 2.0

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

JavaScript

C, Java, Python

C and C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux

hosted

Android
iOS
Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

Standard with numerous extensions

Standard SQL with extensions for time-series applications

APIs and other access methods

JavaScript API

ADO.NET
C API
JDBC
ODBC

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

Proprietary native API

JDBC
RESTful HTTP API

Supported programming languages

JavaScript

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

online/offline synchronization between client and server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

yes

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 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

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7 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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