DBMS > Amazon DocumentDB vs. Cachelot.io vs. Microsoft SQL Server vs. StarRocks

System Properties Comparison Amazon DocumentDB vs. Cachelot.io vs. Microsoft SQL Server vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

In-memory caching system

Microsofts flagship relational DBMS

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Document store

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

aws.amazon.com/documentdb

cachelot.io

www.microsoft.com/en-us/sql-server

www.starrocks.io

Technical documentation

aws.amazon.com/documentdb/resources

learn.microsoft.com/en-US/sql/sql-server

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Microsoft

The Linux Foundation

since Feb 2023

Initial release

2019

2015

1989

2020

Current release

SQL Server 2022, November 2022

2.5.3, March 2023

License

Commercial or Open Source

commercial

Open Source

Simplified BSD License

commercial

restricted free version is available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
Windows

Linux

Data scheme

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Memcached protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
MySQL protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Java

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

yes, but depending on the SQL-Server Edition

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

none

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document 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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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