DBMS > GigaSpaces vs. Microsoft Azure Cosmos DB vs. Oracle vs. Rockset

System Properties Comparison GigaSpaces vs. Microsoft Azure Cosmos DB vs. Oracle vs. Rockset

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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

Globally distributed, horizontally scalable, multi-model database service

Widely used RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store

Secondary database models

Graph DBMS
Search engine

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Relational DBMS
Search engine

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

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Website

www.gigaspaces.com

azure.microsoft.com/services/cosmos-db

www.oracle.com/database

rockset.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/database

docs.rockset.com

Developer

Gigaspaces Technologies

Microsoft

Oracle

Rockset

Initial release

2000

2014

1980

2019

Current release

15.5, September 2020

23c, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

restricted free version is available

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

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

hosted

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

All properties auto-indexed by default

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

yes

with proprietary extensions

Read-only SQL queries, including JOINs

APIs and other access methods

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

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

HTTP REST

Supported programming languages

.Net
C++
Java
Python
Scala

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes, event driven architecture

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

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

Integration with Hadoop/HDInsight on Azure*

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual 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

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Role-based access control

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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