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

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

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	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

blueflood.io

azure.microsoft.com/services/cosmos-db

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

rethinkdb.com

tempoiq.com (offline)

Technical documentation

github.com/rax-maas/blueflood/wiki

learn.microsoft.com/azure/cosmos-db

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

rethinkdb.com/docs

Developer

Rackspace

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

The Linux Foundation

since July 2017

TempoIQ

Initial release

2013

2014

1984

2009

2012

Current release

7.4.1.1, 2021

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

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++

Server operating systems

Linux
OS X

hosted

HP Open VMS

Linux
OS X
Windows

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

yes

string, binary, float, bool, date, geometry

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

yes

APIs and other access methods

HTTP REST

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

HTTP API

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Client-side triggers through changefeeds

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

Source-replica replication

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

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

yes, on a single node

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

User concepts

Access control

Access rights can be defined down to the item level

yes

users and table-level permissions

simple authentication-based access control

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