DBMS > Alibaba Cloud MaxCompute vs. IRONdb vs. RRDtool vs. SAP HANA vs. Trafodion

System Properties Comparison Alibaba Cloud MaxCompute vs. IRONdb vs. RRDtool vs. SAP HANA vs. Trafodion

Editorial information provided by DB-Engines

Name

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

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

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

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

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.

In-memory, column based data store. Available as appliance or cloud service

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.alibabacloud.com/product/maxcompute

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

oss.oetiker.ch/rrdtool

www.sap.com/products/hana.html

trafodion.apache.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

oss.oetiker.ch/rrdtool/doc

help.sap.com/hana

trafodion.apache.org/documentation.html

Developer

Alibaba

Circonus LLC.

Tobias Oetiker

SAP

Apache Software Foundation, originally developed by HP

Initial release

2016

2017

1999

2010

2014

Current release

V0.10.20, January 2018

1.8.0, 2022

2.0 SPS07 (April 4, 2023), April 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL V2 and FLOSS

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

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

C++, Java

Server operating systems

hosted

Linux

HP-UX
Linux

Appliance or cloud-service

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

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

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

HTTP API

in-process shared library
Pipes

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

Java

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

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

in Java

yes, in Lua

SQLScript, R

Java Stored Procedures

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

yes

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

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

none

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

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

fine grained access rights according to SQL-standard

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