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

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

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

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

Port of SQLite to JavaScript

Primary database model

Graph DBMS
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

bitnine.net/agensgraph

www.gridgain.com

www.snowflake.com

sql.js.org

Technical documentation

bitnine.net/documentation

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

sql.js.org/documentation/index.html

Developer

Bitnine Global Inc.

GridGain Systems, Inc.

Snowflake Computing Inc.

Alon Zakai

enhancements implemented by others

Initial release

2016

2007

2014

2012

Current release

2.1, December 2018

GridGain 8.5.1

License

Commercial or Open Source

Open Source

Apache License 2.0

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
Windows

Linux
OS X
Solaris
Windows

hosted

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

Data scheme

depending on used data model

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

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

SQL-92 is not fully supported

APIs and other access methods

Cypher Query Language
JDBC

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

CLI Client
JDBC
ODBC

JavaScript API

Supported programming languages

C
Java
JavaScript
Python

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

yes

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

user defined functions

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes (replicated cache)

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

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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

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