DBMS > InfinityDB vs. MySQL vs. Quasardb vs. Rockset vs. Titan

System Properties Comparison InfinityDB vs. MySQL vs. Quasardb vs. Rockset 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

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

Widely used open source RDBMS

Distributed, high-performance timeseries database

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Time Series DBMS

Document store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS
Search engine

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

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

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

github.com/thinkaurelius/titan

Technical documentation

boilerbay.com/infinitydb/manual

dev.mysql.com/doc

doc.quasar.ai/master

docs.rockset.com

github.com/thinkaurelius/titan/wiki

Developer

Boiler Bay Inc.

Oracle

since 2010, originally MySQL AB, then Sun

quasardb

Rockset

Aurelius, owned by DataStax

Initial release

2002

1995

2009

2019

2012

Current release

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

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

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Implementation language

Java

C and C++

C++

Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

hosted

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

dynamic typing

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

ingestion from XML files supported

Secondary indexes

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

yes

with tags

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

Read-only SQL queries, including JOINs

APIs and other access methods

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

HTTP REST

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

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

Automatic sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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 with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

Access rights for users and organizations can be defined via Rockset console

User authentification and security via Rexster Graph Server

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