DBMS > atoti vs. ITTIA vs. LeanXcale vs. Titan

System Properties Comparison atoti vs. ITTIA vs. LeanXcale vs. Titan

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Editorial information provided by DB-Engines

Name

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Edge Time Series DBMS with Real-Time Stream Processing

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Object oriented DBMS

Time Series DBMS

Key-value store
Relational DBMS

Graph DBMS

Secondary database models

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.39
Rank	#273	Overall
	#24	Time Series DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Website

atoti.io

www.ittia.com

www.leanxcale.com

github.com/thinkaurelius/titan

Technical documentation

docs.atoti.io

github.com/thinkaurelius/titan/wiki

Developer

ActiveViam

ITTIA L.L.C.

LeanXcale

Aurelius, owned by DataStax

Initial release

2007

2015

2012

Current release

8.7

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache license, version 2.0

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 and C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Fixed schema

yes

Typing

predefined data types such as float or date

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through Apache Derby

APIs and other access methods

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C++
JavaScript (Node.js)
Python

C
Java
Scala

Clojure
Java
Python

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

Database file passwords

User authentification and security via Rexster Graph Server

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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

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