DBMS > Alibaba Cloud Table Store vs. HugeGraph vs. Quasardb vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison Alibaba Cloud Table Store vs. HugeGraph vs. Quasardb vs. RocksDB vs. SAP SQL Anywhere

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

A fast-speed and highly-scalable Graph DBMS

Distributed, high-performance timeseries database

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.alibabacloud.com/product/table-store

github.com/hugegraph
hugegraph.apache.org

quasar.ai

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

hugegraph.apache.org/docs

doc.quasar.ai/master

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Alibaba

Baidu

quasardb

Facebook, Inc.

SAP

formerly Sybase

Initial release

2016

2018

2009

2013

1992

Current release

0.9

3.14.1, January 2024

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

BSD

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

C++

Server operating systems

hosted

Linux
macOS
Unix

BSD
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

Java
Python

Groovy
Java
Python

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

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

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

Sharding

consistent hashing

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

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

Source-replica replication with selectable replication factor

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Users, roles and permissions

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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