DBMS > GridGain vs. Microsoft Access vs. Snowflake

System Properties Comparison GridGain vs. Microsoft Access vs. Snowflake

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Name

Description

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

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Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.gridgain.com

www.microsoft.com/en-us/microsoft-365/access

www.snowflake.com

Technical documentation

www.gridgain.com/docs/index.html

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

Developer

GridGain Systems, Inc.

Microsoft

Snowflake Computing Inc.

Initial release

2007

1992

2014

Current release

GridGain 8.5.1

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

yes

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

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

yes

but not compliant to any SQL standard

yes

APIs and other access methods

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

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes (cache interceptors and events)

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

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

a simple user-level security was built in till version Access 2003

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

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