DBMS > GigaSpaces vs. Google BigQuery vs. IBM Cloudant vs. Postgres-XL vs. SAP SQL Anywhere

System Properties Comparison GigaSpaces vs. Google BigQuery vs. IBM Cloudant vs. Postgres-XL vs. SAP SQL Anywhere

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

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Document store

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Spatial DBMS

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

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

www.gigaspaces.com

cloud.google.com/bigquery

www.ibm.com/products/cloudant

www.postgres-xl.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

www.postgres-xl.org/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Gigaspaces Technologies

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

SAP

formerly Sybase

Initial release

2000

2010

2014

since 2012, originally named StormDB

1992

Current release

15.5, September 2020

10 R1, October 2018

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

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

Erlang

Server operating systems

Linux
macOS
Solaris
Windows

hosted

Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

schema-free

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.

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

RESTful HTTP/JSON API

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

atomic operations within a document possible

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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