DBMS > NCache vs. PostGIS vs. STSdb vs. Vertica

System Properties Comparison NCache vs. PostGIS vs. STSdb vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

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

Spatial extension of PostgreSQL

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Column oriented

Secondary database models

Document store
Search engine

Using distributed Lucene

Relational DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.91
Rank	#196	Overall
	#29	Key-value stores

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.alachisoft.com/ncache

postgis.net

github.com/STSSoft/STSdb4

www.vertica.com

Technical documentation

www.alachisoft.com/resources/docs

postgis.net/documentation

vertica.com/documentation

Developer

Alachisoft

STS Soft SC

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2005

2011

2005

Current release

5.3.3, April 2024

3.4.2, February 2024

4.0.8, September 2015

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Enterprise Edition available

Open Source

GPL v2.0

Open Source

GPLv2, commercial license available

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#, .NET, .NET Core, Java

C++

Server operating systems

Linux
Windows

Windows

Linux

Data scheme

schema-free

yes

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

primitive types and user defined types (classes)

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

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

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

APIs and other access methods

IDistributedCache
JCache
LINQ
Proprietary native API

.NET Client API

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

character-based, interactive, front-end utility

Supported programming languages

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

C#
Java

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

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

user defined functions

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

yes

based on PostgreSQL

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with selectable consistency level

yes

based on PostgreSQL

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

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

ACID

Concurrency

Support for concurrent manipulation of data

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)

yes

based on PostgreSQL

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

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more

Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more

Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more

Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more

Market metrics

Market Leader in .NET Distributed Caching since 2005.
» more

Licensing and pricing models

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

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