DBMS > Amazon Redshift vs. IRONdb vs. Lovefield vs. Quasardb vs. Yaacomo

System Properties Comparison Amazon Redshift vs. IRONdb vs. Lovefield vs. Quasardb vs. Yaacomo

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

Large scale data warehouse service for use with business intelligence tools

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

Embeddable relational database for web apps written in pure JavaScript

Distributed, high-performance timeseries database

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

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/redshift

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

google.github.io/lovefield

quasar.ai

yaacomo.com

Technical documentation

docs.aws.amazon.com/redshift

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

github.com/google/lovefield/blob/master/docs/spec_index.md

doc.quasar.ai/master

Developer

Amazon (based on PostgreSQL)

Circonus LLC.

Google

quasardb

Q2WEB GmbH

Initial release

2012

2017

2014

2009

Current release

V0.10.20, January 2018

2.1.12, February 2017

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

JavaScript

C++

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

BSD
Linux
OS X
Windows

Android
Linux
Windows

Data scheme

yes

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

restricted

yes

with tags

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

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

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

HTTP API

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in Lua

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

none

Sharding

consistent hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

none

Source-replica replication with selectable replication factor

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

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

Transient mode

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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