DBMS > AnzoGraph DB vs. Apache IoTDB vs. MySQL vs. RRDtool vs. Trafodion

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. MySQL vs. RRDtool vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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 open source RDBMS

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Transactional SQL-on-Hadoop DBMS

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

cambridgesemantics.com/anzograph

iotdb.apache.org

www.mysql.com

oss.oetiker.ch/rrdtool

trafodion.apache.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

dev.mysql.com/doc

oss.oetiker.ch/rrdtool/doc

trafodion.apache.org/documentation.html

Developer

Cambridge Semantics

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Tobias Oetiker

Apache Software Foundation, originally developed by HP

Initial release

2018

1995

1999

2014

Current release

2.3, January 2021

1.1.0, April 2023

8.4.0, April 2024

1.8.0, 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V2 and FLOSS

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Implementations in Java (e.g. RRD4J) and C# available

C++, Java

Server operating systems

Linux

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
OS X
Solaris
Windows

HP-UX
Linux

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
Native API

ADO.NET
JDBC
ODBC
Proprietary native API

in-process shared library
Pipes

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

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

Multi-source replication
Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Integration with Hadoop and Spark

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

by using the rrdcached daemon

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

yes

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.