DBMS > Amazon Redshift vs. Apache Jena - TDB vs. Drizzle vs. HEAVY.AI

System Properties Comparison Amazon Redshift vs. Apache Jena - TDB vs. Drizzle vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Primary database model

Relational DBMS

RDF store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

aws.amazon.com/redshift

jena.apache.org/documentation/tdb/index.html

github.com/heavyai/heavydb
www.heavy.ai

Technical documentation

docs.aws.amazon.com/redshift

jena.apache.org/documentation/tdb/index.html

docs.heavy.ai

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

originally developed by HP Labs

Drizzle project, originally started by Brian Aker

HEAVY.AI, Inc.

Initial release

2012

2000

2008

2016

Current release

4.9.0, July 2023

7.2.4, September 2012

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

Open Source

GNU GPL

Open Source

Apache Version 2; enterprise edition available

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

C++

C++ and CUDA

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
OS X

Linux

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

JDBC

JDBC
ODBC
Thrift
Vega

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

via event handler

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

Multi-source 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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Access control via Jena Security

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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