DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. IRONdb vs. LMDB vs. Microsoft SQL Server vs. Percona Server for MongoDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. IRONdb vs. LMDB vs. Microsoft SQL Server vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A high performant, light-weight, embedded key-value database library

Microsofts flagship relational DBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.60
Rank	#246	Overall
	#39	Document stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

www.circonus.com/solutions/time-series-database/

www.symas.com/symas-embedded-database-lmdb

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

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.circonus.com/irondb/category/getting-started

www.lmdb.tech/doc

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

docs.percona.com/percona-distribution-for-mongodb

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Circonus LLC.

Symas

Microsoft

Percona

Initial release

2016

2017

2011

1989

2015

Current release

V0.10.20, January 2018

0.9.32, January 2024

SQL Server 2022, November 2022

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

commercial

restricted free version is available

Open Source

GPL Version 2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

Server operating systems

hosted

Linux

Linux
Unix
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

JDBC
ODBC

HTTP API

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

proprietary protocol using JSON

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

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

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes

yes, in Lua

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

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic, metric affinity per node

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

configurable replication factor, datacenter aware

none

yes, but depending on the SQL-Server Edition

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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