DBMS > NCache vs. SAP IQ vs. Snowflake vs. Solr

System Properties Comparison NCache vs. SAP IQ vs. Snowflake vs. Solr

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Editorial information provided by DB-Engines

Name

Description

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

Columnar RDBMS optimized for Big Data analytics

Cloud-based data warehousing service for structured and semi-structured data

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

column-oriented

Secondary database models

Document store
Search engine

Using distributed Lucene

Spatial DBMS

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

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

www.alachisoft.com/ncache

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.snowflake.com

solr.apache.org

Technical documentation

www.alachisoft.com/resources/docs

help.sap.com/docs/SAP_IQ

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Developer

Alachisoft

SAP, formerly Sybase

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2005

1994

2014

2006

Current release

5.3.3, April 2024

16.1 SPS04, April 2019

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Enterprise Edition available

commercial

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

partial

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

yes

supports customizable data types and automatic typing

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

All search fields are automatically indexed

SQL

Support of SQL

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

yes

Solr Parallel SQL Interface

APIs and other access methods

IDistributedCache
JCache
LINQ
Proprietary native API

ADO.NET
JDBC
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

yes

user defined functions

Java plugins

Triggers

yes

Notifications

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

yes

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with selectable consistency level

SAP/Sybase Replication Server

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

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

Eventual 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

optimistic locking

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)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

More information provided by the system vendor

Specific characteristics

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
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Competitive advantages

NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
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Typical application scenarios

NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

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

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