DBMS > GridGain vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics

System Properties Comparison GridGain vs. IBM Db2 vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Globally distributed, horizontally scalable, multi-model database service

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

www.gridgain.com

www.ibm.com/products/db2

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

Technical documentation

www.gridgain.com/docs/index.html

www.ibm.com/docs/en/db2

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

Developer

GridGain Systems, Inc.

IBM

Microsoft

Initial release

2007

1983

host version

2014

2016

Current release

GridGain 8.5.1

12.1, October 2016

License

Commercial or Open Source

commercial

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
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

Data scheme

yes

schema-free

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

yes

SQL-like query language

yes

APIs and other access methods

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

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

C#
Java
PHP

Server-side scripts

Stored procedures

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

yes

JavaScript

Transact SQL

Triggers

yes (cache interceptors and events)

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

with separate tools (MQ, InfoSphere)

yes

Implicit feature of the cloud service

yes

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*

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

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

yes

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