DBMS > Alibaba Cloud Table Store vs. GBase vs. gStore vs. RRDtool

System Properties Comparison Alibaba Cloud Table Store vs. GBase vs. gStore vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

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

A native Graph DBMS to store and maintain very large RDF datasets.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

www.alibabacloud.com/product/table-store

www.gbase.cn

en.gstore.cn

oss.oetiker.ch/rrdtool

Technical documentation

www.alibabacloud.com/help/en/tablestore

en.gstore.cn/#/enDocs

oss.oetiker.ch/rrdtool/doc

Developer

Alibaba

General Data Technology Co., Ltd.

Tobias Oetiker

Initial release

2016

2004

2016

1999

Current release

GBase 8a, GBase 8s, GBase 8c

1.2, November 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

GPL V2 and FLOSS

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, Java, Python

C++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux

HP-UX
Linux

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

APIs and other access methods

HTTP API

ADO.NET
C API
JDBC
ODBC

HTTP API
SPARQL 1.1

in-process shared library
Pipes

Supported programming languages

Java
Python

C++
Java
JavaScript (Node.js)
PHP
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Transaction concepts

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

Atomic single-row operations

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Access rights based on subaccounts and tokens

yes

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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