DBMS > GigaSpaces vs. Google BigQuery vs. OpenEdge vs. Quasardb vs. TimesTen

System Properties Comparison GigaSpaces vs. Google BigQuery vs. OpenEdge vs. Quasardb vs. TimesTen

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

Application development environment with integrated database management system

Distributed, high-performance timeseries database

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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Trend Chart

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

www.gigaspaces.com

cloud.google.com/bigquery

www.progress.com/openedge

quasar.ai

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigquery/docs

documentation.progress.com/output/ua/OpenEdge_latest

doc.quasar.ai/master

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Gigaspaces Technologies

Google

Progress Software Corporation

quasardb

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2000

2010

1984

2009

1998

Current release

15.5, September 2020

OpenEdge 12.2, March 2020

3.14.1, January 2024

Release 22.1

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

Linux
macOS
Solaris
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

BSD
Linux
OS X
Windows

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

close to SQL 92

SQL-like query language

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC

HTTP API

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

.Net
C++
Java
Python
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Progress proprietary ABL (Advanced Business Language)

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

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

PL/SQL

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

since Version 11.4

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

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)

Users and groups

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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