DBMS > Datomic vs. Postgres-XL vs. SAP HANA vs. Valentina Server

System Properties Comparison Datomic vs. Postgres-XL vs. SAP HANA vs. Valentina Server

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Object-relational database and reports server

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Website

www.datomic.com

www.postgres-xl.org

www.sap.com/products/hana.html

www.valentina-db.net

Technical documentation

docs.datomic.com

www.postgres-xl.org/documentation

help.sap.com/hana

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Cognitect

SAP

Paradigma Software

Initial release

2012

2014

since 2012, originally named StormDB

2010

1999

Current release

1.0.7075, December 2023

10 R1, October 2018

2.0 SPS07 (April 4, 2023), April 2023

5.7.5

License

Commercial or Open Source

commercial

limited edition free

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

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

Linux
macOS

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

ODBC

Supported programming languages

Clojure
Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

SQLScript, R

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

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

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

MVCC

ACID

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

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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