DBMS > Amazon Redshift vs. Apache Jena - TDB vs. etcd vs. eXtremeDB vs. HugeGraph

System Properties Comparison Amazon Redshift vs. Apache Jena - TDB vs. etcd vs. eXtremeDB vs. HugeGraph

Editorial information provided by DB-Engines

Name

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

A distributed reliable key-value store

Natively in-memory DBMS with options for persistency, high-availability and clustering

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

RDF store

Key-value store

Relational DBMS
Time Series DBMS

Graph 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	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

aws.amazon.com/redshift

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

etcd.io
github.com/etcd-io/etcd

www.mcobject.com

github.com/hugegraph
hugegraph.apache.org

Technical documentation

docs.aws.amazon.com/redshift

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.mcobject.com/docs/extremedb.htm

hugegraph.apache.org/docs

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

originally developed by HP Labs

McObject

Baidu

Initial release

2012

2000

2001

2018

Current release

4.9.0, July 2023

3.4, August 2019

8.2, 2021

0.9

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Java

Server operating systems

hosted

All OS with a Java VM

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS
Unix

Data scheme

yes

RDF Schemas

schema-free

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.

support of XML interfaces available

Secondary indexes

restricted

yes

also supports composite index and range index

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with the option: eXtremeSQL

APIs and other access methods

JDBC
ODBC

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

gRPC
JSON over HTTP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C#
C++
Java
Lua
Python
Scala

Groovy
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

asynchronous Gremlin script jobs

Triggers

yes

via event handler

yes, watching key changes

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning / sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

edges in graph

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Users, roles and permissions

More information provided by the system vendor

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