DBMS > BigObject vs. Blueflood vs. Realm

System Properties Comparison BigObject vs. Blueflood vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store

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

Score	0.03
Rank	#341	Overall
	#152	Relational DBMS

Score	0.00
Rank	#357	Overall
	#33	Time Series DBMS

Score	9.82
Rank	#50	Overall
	#9	Document stores

Website

bigobject.io

blueflood.io

realm.io

Technical documentation

docs.bigobject.io

github.com/rackerlabs/blueflood/wiki

realm.io/docs

Developer

BigObject, Inc.

Rackspace

Realm, acquired by MongoDB in May 2019

Initial release

2015

2013

2014

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

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

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Android
Backend: server-less
iOS
Windows

Data scheme

yes

predefined scheme

yes

Typing

predefined data types such as float or date

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 DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Lua

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

In-Memory realm

User concepts

Access control

yes

More information provided by the system vendor

Specific characteristics

Now a part of MongoDB Data Platform , Realm Database is the fast, easy to use, and...
» more

Competitive advantages

Realm ensures offline-first functionality, meaning apps run smoothly and deliver...
» more

Typical application scenarios

Mobile Consumer Apps First-Line Worker Apps
» more

Key customers

Cathay Pacific Royal Carribbean Cruise Lines Open Source Database powers apps built...
» more

Market metrics

Used by 100,000+ developers 2 bn installs Currently used in 40k+ applications in...
» more

Licensing and pricing models

Realm database is licensed under the Apache License v2.0.
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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