DBMS > Blueflood vs. CrateDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB

System Properties Comparison Blueflood vs. CrateDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Distributed Date Store based on Lucene

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Time Series DBMS

Relational DBMS
Search engine

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Time Series DBMS

Spatial DBMS

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

Score	0.02
Rank	#344	Overall
	#31	Time Series DBMS

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	18.92
Rank	#39	Overall
	#6	Document stores

Score	40.22
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

blueflood.io

crate.io

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/rackerlabs/blueflood/wiki

crate.io/docs

firebase.google.com/docs/database

docs.microsoft.com/azure/cosmos-db

Developer

Rackspace

Crate

Google

acquired by Google 2014

Microsoft

Initial release

2013

2012

2014

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

Server operating systems

Linux
OS X

All OS with a Java 7 (and higher) VM

hosted

Data scheme

predefined scheme

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

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

SQL

Support of SQL

yes, but no triggers and constraints

SQL-like query language

APIs and other access methods

HTTP REST

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

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

Supported programming languages

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

Java
JavaScript
Objective-C

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

Server-side scripts

Stored procedures

user defined functions

limited functionality with using 'rules'

JavaScript

Triggers

Callbacks are triggered when data changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

yes

Multi-item ACID transactions with snapshot isolation within a partition

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

rights management via user accounts

yes, based on authentication and database rules

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

CrateDB is an open source distributed SQL database that spreads data and processing...
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Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
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Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more

Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more

Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more

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