DBMS > Apache Impala vs. RDF4J vs. SAP HANA vs. TDSQL for MySQL

System Properties Comparison Apache Impala vs. RDF4J vs. SAP HANA vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for 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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Document store

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

impala.apache.org

rdf4j.org

www.sap.com/products/hana.html

www.tencentcloud.com/products/dcdb

Technical documentation

impala.apache.org/impala-docs.html

rdf4j.org/documentation

help.sap.com/hana

www.tencentcloud.com/document/product/1042

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

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

SAP

Tencent

Initial release

2013

2004

2010

2013

Current release

4.1.0, June 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

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

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Appliance or cloud-service

hosted

Data scheme

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC

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 supporting JDBC/ODBC

Java
PHP
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

SQLScript, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Multi-source replication
Source-replica replication

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

Users with fine-grained authorization concept

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