DBMS > Amazon DocumentDB vs. Graphite vs. Microsoft SQL Server vs. searchxml vs. TimescaleDB

System Properties Comparison Amazon DocumentDB vs. Graphite vs. Microsoft SQL Server vs. searchxml vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Microsofts flagship relational DBMS

DBMS for structured and unstructured content wrapped with an application server

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store

Time Series DBMS

Relational DBMS

Native XML DBMS
Search engine

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

aws.amazon.com/documentdb

github.com/graphite-project/graphite-web

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

www.searchxml.net/category/products

www.timescale.com

Technical documentation

aws.amazon.com/documentdb/resources

graphite.readthedocs.io

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

www.searchxml.net/support/handouts

docs.timescale.com

Developer

Chris Davis

Microsoft

informationpartners gmbh

Timescale

Initial release

2019

2006

1989

2015

2017

Current release

SQL Server 2022, November 2022

1.0

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Python

C++

Server operating systems

hosted

Linux
Unix

Linux
Windows

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

full PostgreSQL SQL syntax

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP API
Sockets

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

RESTful HTTP API
WebDAV
XQuery
XSLT

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

JavaScript (Node.js)
Python

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

C++

most other programming languages supported via APIs

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

yes

on the application server

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

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

none

yes, across time and space (hash partitioning) attributes

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

yes

sychronisation to multiple collections

Source-replica replication with hot standby and reads on replicas

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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

Domain, group and role-based access control at the document level and for application services

fine grained access rights according to SQL-standard

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