DBMS > Alibaba Cloud Table Store vs. FatDB vs. HugeGraph vs. STSdb vs. TimesTen

System Properties Comparison Alibaba Cloud Table Store vs. FatDB vs. HugeGraph vs. STSdb vs. TimesTen

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

In-Memory RDBMS compatible to Oracle

Primary database model

Wide column store

Document store
Key-value store

Graph DBMS

Key-value store

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	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/hugegraph
hugegraph.apache.org

github.com/STSSoft/STSdb4

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

hugegraph.apache.org/docs

docs.oracle.com/database/timesten-18.1

Developer

Alibaba

FatCloud

Baidu

STS Soft SC

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2012

2018

2011

1998

Current release

0.9

4.0.8, September 2015

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

commercial

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

Server operating systems

hosted

Windows

Linux
macOS
Unix

Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

also supports composite index and range index

yes

SQL

Support of SQL

Via inetgration in SQL Server

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

.NET Client API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
Python

Groovy
Java
Python

C#
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

via applications

asynchronous Gremlin script jobs

PL/SQL

Triggers

yes

via applications

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

none

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

none

Multi-source replication
Source-replica replication

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 or Eventual Consistency depending on configuration

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

by means of logfiles and checkpoints

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

Can implement custom security layer via applications

Users, roles and permissions

fine grained access rights according to SQL-standard

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache Software Foundation Announces New Top-Level Project Apache Paimon
16 April 2024, Datanami

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

Top 5 CVEs and Vulnerabilities of May 2024
3 June 2024, Security Boulevard

provided by Google News

Share this page