DBMS > GigaSpaces vs. IRONdb vs. Quasardb vs. Snowflake

System Properties Comparison GigaSpaces vs. IRONdb vs. Quasardb vs. Snowflake

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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.

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Distributed, high-performance timeseries database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.gigaspaces.com

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

quasar.ai

www.snowflake.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

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

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

Developer

Gigaspaces Technologies

Circonus LLC.

quasardb

Snowflake Computing Inc.

Initial release

2000

2017

2009

2014

Current release

15.5, September 2020

V0.10.20, January 2018

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

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

Java, C++, .Net

C and C++

C++

Server operating systems

Linux
macOS
Solaris
Windows

Linux

BSD
Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL-99 for query and DML statements

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

SQL-like query language

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes, in Lua

user defined functions

Triggers

yes, event driven architecture

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

configurable replication factor, datacenter aware

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

User concepts

Access control

Role-based access control

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept, user roles and pluggable authentication

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