DBMS > Blazegraph vs. KairosDB vs. OrigoDB vs. TempoIQ

System Properties Comparison Blazegraph vs. KairosDB vs. OrigoDB vs. TempoIQ

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Distributed Time Series DBMS based on Cassandra or H2

A fully ACID in-memory object graph database

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Document store
Object oriented DBMS

Time Series DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

blazegraph.com

github.com/kairosdb/kairosdb

origodb.com

tempoiq.com (offline)

Technical documentation

wiki.blazegraph.com

kairosdb.github.io

origodb.com/docs

Developer

Blazegraph

Robert Friberg et al

TempoIQ

Initial release

2006

2013

2009

under the name LiveDB

2012

Current release

2.1.5, March 2019

1.2.2, November 2018

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache 2.0

Open Source

commercial

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

Server operating systems

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Graphite protocol
HTTP REST
Telnet API

.NET Client API
HTTP API
LINQ

HTTP API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

.Net

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

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 or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Relationships in Graphs

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

simple password-based access control

Role based authorization

simple authentication-based access control

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More resources

Recent citations in the news

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

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Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

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29 October 2015, Automation World

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