DBMS > Apache IoTDB vs. Microsoft Azure Cosmos DB vs. mSQL vs. Percona Server for MySQL vs. Sphinx

System Properties Comparison Apache IoTDB vs. Microsoft Azure Cosmos DB vs. mSQL vs. Percona Server for MySQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Globally distributed, horizontally scalable, multi-model database service

mSQL (Mini SQL) is a simple and lightweight RDBMS

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

iotdb.apache.org

azure.microsoft.com/services/cosmos-db

hughestech.com.au/products/msql

www.percona.com/software/mysql-database/percona-server

sphinxsearch.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

learn.microsoft.com/azure/cosmos-db

www.percona.com/downloads/Percona-Server-LATEST

sphinxsearch.com/docs

Developer

Apache Software Foundation

Microsoft

Hughes Technologies

Percona

Sphinx Technologies Inc.

Initial release

2018

2014

1994

2008

2001

Current release

1.1.0, April 2023

4.4, October 2021

8.0.36-28, 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free licenses can be provided

Open Source

GPL version 2

Open Source

GPL version 2, commercial licence available

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

Java

C and C++

C++

Server operating systems

All OS with a Java VM (>= 1.8)

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
Native API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

Implicit feature of the cloud service

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

Implicit feature of the cloud service

none

Multi-source replication
Source-replica replication
XtraDB Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

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