DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Linter vs. MonetDB vs. SurrealDB

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Linter vs. MonetDB vs. SurrealDB

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

RDBMS for high security requirements

A relational database management system that stores data in columns

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Wide column store

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.86
Rank	#203	Overall
	#34	Document stores
	#18	Graph DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

linter.ru

www.monetdb.org

surrealdb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

www.monetdb.org/Documentation

surrealdb.com/docs

Developer

Alibaba

Amazon

relex.ru

MonetDB BV

SurrealDB Ltd

Initial release

2016

2012

1990

2004

2022

Current release

Dec2023 (11.49), December 2023

v1.5.0, May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Mozilla Public License 2.0

Open Source

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 C++

Rust

Server operating systems

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

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

yes

SQL 2003 with some extensions

SQL-like query language

APIs and other access methods

HTTP API

RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes, in SQL, C, R

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

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.

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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