DBMS > IRONdb vs. Quasardb vs. SAP HANA vs. Yaacomo

System Properties Comparison IRONdb vs. Quasardb vs. SAP HANA vs. Yaacomo

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Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Distributed, high-performance timeseries database

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

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

quasar.ai

www.sap.com/products/hana.html

yaacomo.com

Technical documentation

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

doc.quasar.ai/master

help.sap.com/hana

Developer

Circonus LLC.

quasardb

SAP

Q2WEB GmbH

Initial release

2017

2009

2010

2009

Current release

V0.10.20, January 2018

3.14.1, January 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

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

commercial

Cloud-based only

Only available as a cloud service

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++

Server operating systems

Linux

BSD
Linux
OS X
Windows

Appliance or cloud-service

Android
Linux
Windows

Data scheme

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

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

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

Server-side scripts

Stored procedures

yes, in Lua

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

Sharding

consistent hashing

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

Source-replica replication with selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

Cryptographically strong user authentication and audit trail

yes

fine grained access rights according to SQL-standard

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