DBMS > Hypertable vs. NCache vs. SQLite vs. SQream DB vs. Stardog

System Properties Comparison Hypertable vs. NCache vs. SQLite vs. SQream DB vs. Stardog

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

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

a GPU-based, columnar RDBMS for big data analytics workloads

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.alachisoft.com/ncache

www.sqlite.org

sqream.com

www.stardog.com

Technical documentation

www.alachisoft.com/resources/docs

www.sqlite.org/docs.html

docs.sqream.com

docs.stardog.com

Developer

Hypertable Inc.

Alachisoft

Dwayne Richard Hipp

SQream Technologies

Stardog-Union

Initial release

2009

2005

2000

2017

2010

Current release

0.9.8.11, March 2016

5.3.3, April 2024

3.45.3 (15 April 2024), April 2024

2022.1.6, December 2022

7.3.0, May 2020

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Enterprise Edition available

Open Source

Public Domain

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

server-less

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

dynamic column types

yes

schema-free and OWL/RDFS-schema support

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, ANSI Standard SQL Types

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.

Import/export of XML data possible

Secondary indexes

restricted

only exact value or prefix value scans

yes

supports real-time indexing in full-text and geospatial

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

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

C++ API
Thrift

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

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

C++
Java
JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

user defined functions in Python

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Notifications

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes, with selectable consistency level

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

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)

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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