DBMS > Amazon DocumentDB vs. Blueflood vs. IRONdb vs. Oracle Rdb

System Properties Comparison Amazon DocumentDB vs. Blueflood vs. IRONdb vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Scalable TimeSeries DBMS based on Cassandra

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Document store

Time Series DBMS

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Website

aws.amazon.com/documentdb

blueflood.io

www.circonus.com/solutions/time-series-database/

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

Technical documentation

aws.amazon.com/documentdb/resources

github.com/rax-maas/blueflood/wiki

docs.circonus.com/irondb/category/getting-started

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

Developer

Rackspace

Circonus LLC.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2019

2013

2017

1984

Current release

V0.10.20, January 2018

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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 and C++

Server operating systems

hosted

Linux
OS X

Linux

HP Open VMS

Data scheme

schema-free

predefined scheme

schema-free

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

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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 language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

HTTP REST

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes, in Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

based on Cassandra

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

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.

User concepts

Access control

Access rights for users and roles

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More resources

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