DBMS > OrigoDB vs. ReductStore vs. TempoIQ vs. Titan

System Properties Comparison OrigoDB vs. ReductStore vs. TempoIQ vs. Titan

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

A fully ACID in-memory object graph database

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Document store
Object oriented DBMS

Time Series DBMS

Graph DBMS

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

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

origodb.com

github.com/reductstore
www.reduct.store

tempoiq.com (offline)

github.com/thinkaurelius/titan

Technical documentation

origodb.com/docs

www.reduct.store/docs

github.com/thinkaurelius/titan/wiki

Developer

Robert Friberg et al

ReductStore LLC

TempoIQ

Aurelius, owned by DataStax

Initial release

2009

under the name LiveDB

2023

2012

Current release

1.9, March 2024

License

Commercial or Open Source

Open Source

Business Source License 1.1

commercial

Open Source

Apache license, version 2.0

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

C++, Rust

Java

Server operating systems

Linux
Windows

Docker
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

APIs and other access methods

.NET Client API
HTTP API
LINQ

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net

C++
JavaScript (Node.js)
Python
Rust

C#
Java
JavaScript

Node.js
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Relationships in graph

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

User concepts

Access control

Role based authorization

simple authentication-based access control

User authentification and security via Rexster Graph Server

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database
24 August 2015, AWS Blog

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

Beyond Titan: The Evolution of DataStax’s New Graph Database
21 June 2016, Datanami

Database Deep Dives: JanusGraph
8 August 2019, IBM

TigerGraph, a graph database born to roar
19 September 2017, ZDNet

provided by Google News

Share this page