DBMS > Blueflood vs. NCache vs. ObjectBox vs. Splice Machine vs. Trafodion

System Properties Comparison Blueflood vs. NCache vs. ObjectBox vs. Splice Machine 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

Scalable TimeSeries DBMS based on Cassandra

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

Extremely fast embedded database for small devices, IoT and Mobile

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Transactional SQL-on-Hadoop DBMS

Primary database model

Secondary database models

Document store
Search engine

Using distributed Lucene

Time Series DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

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

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

blueflood.io

www.alachisoft.com/ncache

objectbox.io

splicemachine.com

trafodion.apache.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.alachisoft.com/resources/docs

docs.objectbox.io

splicemachine.com/how-it-works

trafodion.apache.org/documentation.html

Developer

Rackspace

Alachisoft

ObjectBox Limited

Splice Machine

Apache Software Foundation, originally developed by HP

Initial release

2013

2005

2017

2014

Current release

5.3.3, April 2024

3.1, March 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Enterprise Edition available

Open Source

Apache License 2.0

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C#, .NET, .NET Core, Java

C and C++

Java

C++, Java

Server operating systems

Linux
OS X

Linux
Windows

Android
iOS
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

predefined scheme

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

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

SQL

Support of SQL

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

yes

APIs and other access methods

HTTP REST

IDistributedCache
JCache
LINQ
Proprietary native API

Proprietary native API

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

support for stored procedures with SQL-Server CLR

yes

Java

Java Stored Procedures

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, with selectable consistency level

online/offline synchronization between client and server

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, multi-version concurrency control (MVCC)

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

Access rights for users, groups and roles according to SQL-standard

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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