DBMS > Hypertable vs. NCache vs. Oracle Rdb vs. SQLite vs. Titan

System Properties Comparison Hypertable vs. NCache vs. Oracle Rdb vs. SQLite vs. Titan

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is 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

An open source BigTable implementation based on distributed file systems such as Hadoop

Open-Source and Enterprise in-memory Key-Value Store

Widely used embeddable, in-process RDBMS

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

www.alachisoft.com/ncache

www.oracle.com/database/technologies/related/rdb.html

www.sqlite.org

github.com/thinkaurelius/titan

Technical documentation

www.alachisoft.com/resources/docs

www.oracle.com/database/technologies/related/rdb-doc.html

www.sqlite.org/docs.html

github.com/thinkaurelius/titan/wiki

Developer

Hypertable Inc.

Alachisoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Dwayne Richard Hipp

Aurelius, owned by DataStax

Initial release

2009

2005

1984

2000

2012

Current release

0.9.8.11, March 2016

5.3.3, April 2024

7.4.1.1, 2021

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Enterprise Edition available

commercial

Open Source

Public Domain

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

C++

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

HP Open VMS

server-less

Linux
OS X
Unix
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

dynamic column types

yes

Typing

predefined data types such as float or date

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

yes

not rigid because of 'dynamic typing' concept.

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

SQL-92 is not fully supported

APIs and other access methods

C++ API
Thrift

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Clojure
Java
Python

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes, with selectable consistency level

none

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
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

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

optimistic locking and pessimistic locking

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

User authentification and security via Rexster Graph Server

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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