DBMS > GridGain vs. Ingres vs. Snowflake vs. SQL.JS

System Properties Comparison GridGain vs. Ingres vs. Snowflake vs. SQL.JS

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Editorial information provided by DB-Engines

Name

Description

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

Well established RDBMS

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

Port of SQLite to JavaScript

Primary database model

Key-value store
Relational DBMS

Relational 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	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

www.gridgain.com

www.actian.com/databases/ingres

www.snowflake.com

sql.js.org

Technical documentation

www.gridgain.com/docs/index.html

docs.actian.com/ingres

docs.snowflake.net/manuals/index.html

sql.js.org/documentation/index.html

Developer

GridGain Systems, Inc.

Actian Corporation

Snowflake Computing Inc.

Alon Zakai

enhancements implemented by others

Initial release

2007

1974

originally developed at University Berkely in early 1970s

2014

2012

Current release

GridGain 8.5.1

11.2, May 2022

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

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

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

Data scheme

yes

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

yes

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

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

yes

Secondary indexes

yes

SQL

Support of SQL

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

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

CLI Client
JDBC
ODBC

JavaScript API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

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

yes

user defined functions

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Ingres Replicator

yes

none

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

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

fine grained access rights according to SQL-standard

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

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