DBMS > IRONdb vs. Microsoft Azure AI Search vs. Quasardb vs. SAP HANA vs. Trafodion

System Properties Comparison IRONdb vs. Microsoft Azure AI Search vs. Quasardb 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

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

Search-as-a-service for web and mobile app development

Distributed, high-performance timeseries database

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

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

azure.microsoft.com/en-us/services/search

quasar.ai

www.sap.com/products/hana.html

trafodion.apache.org

Technical documentation

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

learn.microsoft.com/en-us/azure/search

doc.quasar.ai/master

help.sap.com/hana

trafodion.apache.org/documentation.html

Developer

Circonus LLC.

Microsoft

quasardb

SAP

Apache Software Foundation, originally developed by HP

Initial release

2017

2015

2009

2010

2014

Current release

V0.10.20, January 2018

3.14.1, January 2024

2.0 SPS07 (April 4, 2023), April 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

C++

C++, Java

Server operating systems

Linux

hosted

BSD
Linux
OS X
Windows

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

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

SQL-like query language

yes

APIs and other access methods

HTTP API

RESTful HTTP API

HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

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

C#
Java
JavaScript
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes, in Lua

SQLScript, R

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

yes

using Azure authentication

Cryptographically strong user authentication and audit trail

yes

fine grained access rights according to SQL-standard

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