DBMS > GridGain vs. Microsoft Azure Cosmos DB vs. SAP IQ vs. Snowflake vs. SQL.JS

System Properties Comparison GridGain vs. Microsoft Azure Cosmos DB vs. SAP IQ vs. Snowflake vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Globally distributed, horizontally scalable, multi-model database service

Columnar RDBMS optimized for Big Data analytics

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

Port of SQLite to JavaScript

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

column-oriented

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

www.gridgain.com

azure.microsoft.com/services/cosmos-db

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

sql.js.org

Technical documentation

www.gridgain.com/docs/index.html

learn.microsoft.com/azure/cosmos-db

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

sql.js.org/documentation/index.html

Developer

GridGain Systems, Inc.

Microsoft

SAP, formerly Sybase

Snowflake Computing Inc.

Alon Zakai

enhancements implemented by others

Initial release

2007

2014

1994

2014

2012

Current release

GridGain 8.5.1

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

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

JavaScript

Server operating systems

Linux
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

hosted

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

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

JSON types

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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

JavaScript API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

yes

user defined functions

Triggers

yes (cache interceptors and events)

JavaScript

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Implicit feature of the cloud service

SAP/Sybase Replication Server

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

none

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

Durability

Support for making data persistent

yes

except by serializing a db to a file

In-memory capabilities

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

yes

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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

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