DBMS > IBM Db2 Event Store vs. NCache vs. NSDb vs. SwayDB vs. Trafodion

System Properties Comparison IBM Db2 Event Store vs. NCache vs. NSDb vs. SwayDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed Event Store optimized for Internet of Things use cases

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Transactional SQL-on-Hadoop DBMS

Primary database model

Event Store
Time Series DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.ibm.com/products/db2-event-store

www.alachisoft.com/ncache

nsdb.io

swaydb.simer.au

trafodion.apache.org

Technical documentation

www.ibm.com/docs/en/db2-event-store

www.alachisoft.com/resources/docs

nsdb.io/Architecture

trafodion.apache.org/documentation.html

Developer

IBM

Alachisoft

Simer Plaha

Apache Software Foundation, originally developed by HP

Initial release

2017

2005

2017

2018

2014

Current release

2.0

5.3.3, April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Enterprise Edition available

Open Source

Apache Version 2.0

Open Source

GNU Affero GPL V3.0

Open Source

Apache 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 and C++

C#, .NET, .NET Core, Java

Java, Scala

Scala

C++, Java

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

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

yes: int, bigint, decimal, string

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

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

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

SQL-like query language

yes

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

IDistributedCache
JCache
LINQ
Proprietary native API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

Java
Scala

Java
Kotlin
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

Java Stored Procedures

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, with selectable consistency level

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

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

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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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