DBMS > 4D vs. InfinityDB vs. MySQL vs. Quasardb vs. Titan

System Properties Comparison 4D vs. InfinityDB vs. MySQL vs. Quasardb vs. Titan

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

Application development environment with integrated database management system

A Java embedded Key-Value Store which extends the Java Map interface

Widely used open source RDBMS

Distributed, high-performance timeseries database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Graph DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

github.com/thinkaurelius/titan

Technical documentation

developer.4d.com

boilerbay.com/infinitydb/manual

dev.mysql.com/doc

doc.quasar.ai/master

github.com/thinkaurelius/titan/wiki

Developer

4D, Inc

Boiler Bay Inc.

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Aurelius, owned by DataStax

Initial release

1984

2002

1995

2009

2012

Current release

v20, April 2023

4.0

8.4.0, April 2024

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Java

Server operating systems

OS X
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

integer and binary

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

manual creation possible, using inversions based on multi-value capability

yes

with tags

yes

SQL

Support of SQL

yes

close to SQL 92

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

4D proprietary IDE
PHP

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

consistent hashing

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

not for MyISAM storage engine

yes

Relationships in graph

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using LevelDB

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

Transient mode

User concepts

Access control

Users and groups

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

User authentification and security via Rexster Graph Server

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