DBMS > GigaSpaces vs. Postgres-XL vs. Snowflake

System Properties Comparison GigaSpaces vs. Postgres-XL vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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Trend Chart

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.gigaspaces.com

www.postgres-xl.org

www.snowflake.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Gigaspaces Technologies

Snowflake Computing Inc.

Initial release

2000

2014

since 2012, originally named StormDB

2014

Current release

15.5, September 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Mozilla public license

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

Server operating systems

Linux
macOS
Solaris
Windows

Linux
macOS

hosted

Data scheme

schema-free

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.

XML can be used for describing objects metadata

yes

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

distributed, parallel query execution

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes, event driven architecture

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

Role-based access control

fine grained access rights according to SQL-standard

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

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