DBMS > AnzoGraph DB vs. RRDtool vs. Stardog vs. TimesTen

System Properties Comparison AnzoGraph DB vs. RRDtool vs. Stardog vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

cambridgesemantics.com/anzograph

oss.oetiker.ch/rrdtool

www.stardog.com

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

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

oss.oetiker.ch/rrdtool/doc

docs.stardog.com

docs.oracle.com/database/timesten-18.1

Developer

Cambridge Semantics

Tobias Oetiker

Stardog-Union

Oracle, TimesTen Performance Software, HP

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

Initial release

2018

1999

2010

1998

Current release

2.3, January 2021

1.8.0, 2022

7.3.0, May 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free trial version available

Open Source

GPL V2 and FLOSS

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Linux

HP-UX
Linux

Linux
macOS
Windows

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

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

Numeric data only

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.

Exporting into and restoring from XML files possible

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

in-process shared library
Pipes

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Java
Python

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions and aggregates, HTTP Server extensions in Java

PL/SQL

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate Consistency in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

not needed in graphs

yes

relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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