DBMS > Apache IoTDB vs. GBase vs. MySQL vs. RavenDB vs. searchxml

System Properties Comparison Apache IoTDB vs. GBase vs. MySQL vs. RavenDB vs. searchxml

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Widely used open source RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

www.searchxml.net/category/products

Technical documentation

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

dev.mysql.com/doc

ravendb.net/docs

www.searchxml.net/support/handouts

Developer

Apache Software Foundation

General Data Technology Co., Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

Hibernating Rhinos

informationpartners gmbh

Initial release

2018

2004

1995

2010

2015

Current release

1.1.0, April 2023

GBase 8a, GBase 8s, GBase 8c

8.4.0, April 2024

5.4, July 2022

1.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL version 3, commercial license available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C, Java, Python

C and C++

C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Windows

Data scheme

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

SQL-like query language

Standard with numerous extensions

yes

with proprietary extensions

SQL-like query language (RQL)

APIs and other access methods

JDBC
Native API

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

user defined functions

yes

proprietary syntax

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

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

Multi-source replication
Source-replica replication

Multi-source replication

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID, Cluster-wide transaction available

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

Users with fine-grained authorization concept

no user groups or roles

Authorization levels configured per client per database

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

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