DBMS > AgensGraph vs. AlaSQL vs. RavenDB vs. RDF4J vs. Teradata Aster

System Properties Comparison AgensGraph vs. AlaSQL vs. RavenDB vs. RDF4J vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

JavaScript DBMS library

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Graph DBMS
Relational DBMS

Document store
Relational DBMS

Document store

RDF store

Relational DBMS

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

bitnine.net/agensgraph

alasql.org

ravendb.net

rdf4j.org

Technical documentation

bitnine.net/documentation

github.com/AlaSQL/alasql

ravendb.net/docs

rdf4j.org/documentation

Developer

Bitnine Global Inc.

Andrey Gershun & Mathias R. Wulff

Hibernating Rhinos

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

Teradata

Initial release

2016

2014

2010

2004

2005

Current release

2.1, December 2018

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

MIT-License

Open Source

AGPL version 3, commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

depending on used data model

schema-free

yes

RDF Schemas

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like query language (RQL)

yes

APIs and other access methods

Cypher Query Language
JDBC

JavaScript API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
Java
JavaScript
Python

JavaScript

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

ACID, Cluster-wide transaction available

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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