DBMS > GigaSpaces vs. Ingres vs. Microsoft Azure Cosmos DB vs. Quasardb vs. SQream DB

System Properties Comparison GigaSpaces vs. Ingres vs. Microsoft Azure Cosmos DB vs. Quasardb vs. SQream DB

Editorial information provided by DB-Engines

Name

Description

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

Well established RDBMS

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

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

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

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

www.gigaspaces.com

www.actian.com/databases/ingres

azure.microsoft.com/services/cosmos-db

quasar.ai

sqream.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.actian.com/ingres

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

docs.sqream.com

Developer

Gigaspaces Technologies

Actian Corporation

Microsoft

quasardb

SQream Technologies

Initial release

2000

1974

originally developed at University Berkely in early 1970s

2014

2009

2017

Current release

15.5, September 2020

11.2, May 2022

3.14.1, January 2024

2022.1.6, December 2022

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++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
macOS
Solaris
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

BSD
Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

yes, ANSI Standard SQL Types

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

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All properties auto-indexed by default

yes

with tags

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

.Net
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

user defined functions in Python

Triggers

yes, event driven architecture

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Ingres Replicator

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

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