DBMS > EsgynDB vs. Google BigQuery vs. InterSystems IRIS vs. Microsoft Azure SQL Database vs. TimesTen

System Properties Comparison EsgynDB vs. Google BigQuery vs. InterSystems IRIS vs. Microsoft Azure SQL Database vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Database as a Service offering with high compatibility to Microsoft SQL Server

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.esgyn.cn

cloud.google.com/bigquery

www.intersystems.com/products/intersystems-iris

azure.microsoft.com/en-us/products/azure-sql/database

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

Technical documentation

cloud.google.com/bigquery/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/database/timesten-18.1

Developer

Esgyn

Google

InterSystems

Microsoft

Oracle, TimesTen Performance Software, HP

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

Initial release

2015

2010

2018

2010

1998

Current release

2023.3, June 2023

V12

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

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

C++, Java

C++

Server operating systems

Linux

hosted

AIX
Linux
macOS
Ubuntu
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

depending on used data model

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

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C++
Java
JavaScript (Node.js)
Python

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes

Transact SQL

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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 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

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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