DBMS > GraphDB vs. Heroic vs. PostGIS vs. RocksDB vs. TimesTen

System Properties Comparison GraphDB vs. Heroic vs. PostGIS vs. RocksDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Spatial extension of PostgreSQL

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Relational DBMS

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

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.ontotext.com

github.com/spotify/heroic

postgis.net

rocksdb.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

graphdb.ontotext.com/documentation

spotify.github.io/heroic

postgis.net/documentation

github.com/facebook/rocksdb/wiki

docs.oracle.com/database/timesten-18.1

Social network pages

Developer

Ontotext

Spotify

Facebook, Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2000

2014

2005

2013

1998

Current release

10.4, October 2023

3.4.2, February 2024

9.2.1, May 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

BSD

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

Java

C++

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

yes

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.

yes

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Java API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

user defined functions

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

based on PostgreSQL

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on PostgreSQL

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Eventual Consistency
Immediate Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Constraint checking

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.