DBMS > Datomic vs. Google BigQuery vs. InterSystems IRIS vs. JaguarDB vs. Microsoft Azure Table Storage

System Properties Comparison Datomic vs. Google BigQuery vs. InterSystems IRIS vs. JaguarDB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Performant, highly scalable DBMS for AI and IoT applications

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Key-value store
Vector DBMS

Wide column store

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

Score	1.66
Rank	#144	Overall
	#66	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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

www.datomic.com

cloud.google.com/bigquery

www.intersystems.com/products/intersystems-iris

www.jaguardb.com

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

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

www.jaguardb.com/support.html

Developer

Cognitect

Google

InterSystems

DataJaguar, Inc.

Microsoft

Initial release

2012

2010

2018

2015

2012

Current release

1.0.7075, December 2023

2023.3, June 2023

3.3 July 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

GPL V3.0

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, Clojure

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM

hosted

AIX
Linux
macOS
Ubuntu
Windows

Linux

hosted

Data scheme

yes

depending on used data model

yes

schema-free

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

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

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

rights management via user accounts

Access rights based on private key authentication or shared access signatures

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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