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

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

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Wide column store

Key-value store

Relational DBMS

Column oriented

Secondary database models

Document store
Search engine

Using distributed Lucene

Spatial DBMS
Time Series DBMS

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

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.alachisoft.com/ncache

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

www.sqlite.org

www.vertica.com

Technical documentation

www.alachisoft.com/resources/docs

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

www.sqlite.org/docs.html

vertica.com/documentation

Developer

Hypertable Inc.

Alachisoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Dwayne Richard Hipp

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2009

2005

1984

2000

2005

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

12.0.3, January 2023

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

Enterprise Edition available

commercial

Open Source

Public Domain

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

HP Open VMS

server-less

Linux

Data scheme

schema-free

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

yes

dynamic column types

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

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

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

C++ API
Thrift

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

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

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

Notifications

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

horizontal partitioning, hierarchical partitioning

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

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

Foreign keys

Referential integrity

yes

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

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)

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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Market metrics

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