DBMS > Alibaba Cloud Table Store vs. FatDB vs. HugeGraph vs. jBASE vs. Sadas Engine

System Properties Comparison Alibaba Cloud Table Store vs. FatDB vs. HugeGraph vs. jBASE vs. Sadas Engine

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A fast-speed and highly-scalable Graph DBMS

A robust multi-value DBMS comprising development tools and middleware

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Wide column store

Document store
Key-value store

Graph DBMS

Multivalue DBMS

Relational DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/hugegraph
hugegraph.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.sadasengine.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

hugegraph.apache.org/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Alibaba

FatCloud

Baidu

Rocket Software (formerly Zumasys)

SADAS s.r.l.

Initial release

2016

2012

2018

1991

2006

Current release

0.9

5.7

8.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free trial version 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

Java

C++

Server operating systems

hosted

Windows

Linux
macOS
Unix

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

also supports composite index and range index

yes

SQL

Support of SQL

Via inetgration in SQL Server

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java
Python

Groovy
Java
Python

.Net
Basic
Jabbascript
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes

via applications

asynchronous Gremlin script jobs

yes

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights based on subaccounts and tokens

Can implement custom security layer via applications

Users, roles and permissions

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

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