DBMS > GigaSpaces vs. Google BigQuery vs. Ignite vs. NuoDB vs. SAP SQL Anywhere

System Properties Comparison GigaSpaces vs. Google BigQuery vs. Ignite vs. NuoDB 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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

NuoDB is a webscale distributed database that supports SQL and ACID transactions

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

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.gigaspaces.com

cloud.google.com/bigquery

ignite.apache.org

www.3ds.com/nuodb-distributed-sql-database

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

Technical documentation

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigquery/docs

apacheignite.readme.io/docs

doc.nuodb.com

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Gigaspaces Technologies

Google

Apache Software Foundation

Dassault Systèmes

originally NuoDB, Inc.

SAP

formerly Sybase

Initial release

2000

2010

2015

2013

1992

Current release

15.5, September 2020

Apache Ignite 2.6

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

Apache 2.0

commercial

limited edition free

commercial

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

C++, Java, .Net

C++

Server operating systems

Linux
macOS
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

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

yes

APIs and other access methods

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

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

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

Java, SQL

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

Triggers

yes, event driven architecture

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes (replicated cache)

yes

Managed transparently by NuoDB

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 (compute grid and hadoop accelerator)

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

Since BigQuery is designed for querying data

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

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)

Security Hooks for custom implementations

Standard SQL roles/ privileges, Administrative Users

fine grained access rights according to SQL-standard

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