DBMS > Amazon DocumentDB vs. Microsoft SQL Server vs. RocksDB vs. Sqrrl

System Properties Comparison Amazon DocumentDB vs. Microsoft SQL Server vs. RocksDB vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Microsofts flagship relational DBMS

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

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	#131	Overall
	#24	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

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

Website

aws.amazon.com/documentdb

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

rocksdb.org

sqrrl.com

Technical documentation

aws.amazon.com/documentdb/resources

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

github.com/facebook/rocksdb/wiki

Developer

Microsoft

Facebook, Inc.

Amazon

originally Sqrrl Data, Inc.

Initial release

2019

1989

2013

2012

Current release

SQL Server 2022, November 2022

9.2.1, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

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

C++ API
Java API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

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

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

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes, but depending on the SQL-Server Edition

yes

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

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

yes

Atomic updates per row, document, or graph entity

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

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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