DBMS > Datomic vs. Google BigQuery vs. SAP HANA vs. UniData,UniVerse

System Properties Comparison Datomic vs. Google BigQuery vs. SAP HANA vs. UniData,UniVerse

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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

In-memory, column based data store. Available as appliance or cloud service

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

www.datomic.com

cloud.google.com/bigquery

www.sap.com/products/hana.html

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.datomic.com

cloud.google.com/bigquery/docs

help.sap.com/hana

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Cognitect

Google

SAP

Rocket Software

Initial release

2012

2010

1985

Current release

1.0.6735, June 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

Server operating systems

All OS with a Java VM

hosted

Appliance or cloud-service

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Clojure
Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

in JavaScript

SQLScript, R

yes

Triggers

By using transaction functions

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

configurable

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

Access rights according to SQL-standard and operating system based

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