DBMS > Atos Standard Common Repository vs. HarperDB vs. Hive vs. RDF4J vs. SAP HANA

System Properties Comparison Atos Standard Common Repository vs. HarperDB vs. Hive vs. RDF4J vs. SAP HANA

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Primary database model

Document store
Key-value store

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	0.55
Rank	#248	Overall
	#38	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.harperdb.io

hive.apache.org

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

docs.harperdb.io/docs

cwiki.apache.org/confluence/display/Hive/Home

rdf4j.org/documentation

help.sap.com/hana

Developer

Atos Convergence Creators

HarperDB

Apache Software Foundation

initially developed by Facebook

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

SAP

Initial release

2016

2017

2012

2004

2010

Current release

1703

3.1, August 2021

3.1.3, April 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

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

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Implementation language

Java

Node.js

Java

Server operating systems

Linux

Linux
OS X

All OS with a Java VM

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

Schema and schema-less with LDAP views

dynamic schema

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

optional

yes

JSON data types

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

SQL-like data manipulation statements

SQL-like DML and DDL statements

yes

APIs and other access methods

LDAP

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C++
Java
PHP
Python

Java
PHP
Python

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

user defined functions and integration of map-reduce

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

selectable replication factor

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of specific operations

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

Access rights for users and roles

Access rights for users, groups and roles

yes

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