DBMS > Alibaba Cloud Table Store vs. DataFS vs. Galaxybase vs. LevelDB

System Properties Comparison Alibaba Cloud Table Store vs. DataFS vs. Galaxybase vs. LevelDB

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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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Scalable, ACID-compliant native distributed parallel graph platform

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Primary database model

Secondary database models

Graph DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Website

www.alibabacloud.com/product/table-store

newdatabase.com

galaxybase.com

github.com/google/leveldb

Technical documentation

www.alibabacloud.com/help/en/tablestore

dev.mobiland.com/Overview.xsp

github.com/google/leveldb/blob/main/doc/index.md

Developer

Alibaba

Mobiland AG

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Initial release

2016

2018

2017

2011

Current release

1.1.263, October 2022

Nov 20, November 2021

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

BSD

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 and Java

C++

Server operating systems

hosted

Windows

Linux

Illumos
Linux
OS X
Windows

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

Strong typed schema

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

HTTP API

.NET Client API
Proprietary client DLL
WinRT client

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Supported programming languages

Java
Python

.Net
C
C#
C++
VB.Net

Go
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Server-side scripts

Stored procedures

user defined procedures and functions

Triggers

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Proprietary Sharding system

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Windows-Profile

Role-based access control

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