DBMS > Blueflood vs. Microsoft Azure Cosmos DB vs. NCache vs. Oracle Rdb vs. TempoIQ

System Properties Comparison Blueflood vs. Microsoft Azure Cosmos DB vs. NCache vs. Oracle Rdb vs. TempoIQ

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

Globally distributed, horizontally scalable, multi-model database service

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

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

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

blueflood.io

azure.microsoft.com/services/cosmos-db

www.alachisoft.com/ncache

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

tempoiq.com (offline)

Technical documentation

github.com/rax-maas/blueflood/wiki

learn.microsoft.com/azure/cosmos-db

www.alachisoft.com/resources/docs

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

Developer

Rackspace

Microsoft

Alachisoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

TempoIQ

Initial release

2013

2014

2005

1984

2012

Current release

5.3.3, April 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Enterprise Edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C#, .NET, .NET Core, Java

Server operating systems

Linux
OS X

hosted

Linux
Windows

HP Open VMS

Data scheme

predefined scheme

schema-free

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

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP API

Supported programming languages

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

support for stored procedures with SQL-Server CLR

Triggers

JavaScript

yes

Notifications

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking and pessimistic locking

yes, on a single node

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

Access rights can be defined down to the item level

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

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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

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