DBMS > Badger vs. BigchainDB vs. Google BigQuery vs. KairosDB vs. Realm

System Properties Comparison Badger vs. BigchainDB vs. Google BigQuery vs. KairosDB vs. Realm

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Large scale data warehouse service with append-only tables

Distributed Time Series DBMS based on Cassandra or H2

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

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Website

github.com/dgraph-io/badger

www.bigchaindb.com

cloud.google.com/bigquery

github.com/kairosdb/kairosdb

realm.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigquery/docs

kairosdb.github.io

realm.io/docs

Developer

DGraph Labs

Google

Realm, acquired by MongoDB in May 2019

Initial release

2017

2016

2010

2013

2014

Current release

1.2.2, November 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

Open Source

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

Python

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

hosted

Linux
OS X
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

schema-free

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

yes

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

user defined functions

in JavaScript

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

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

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control

yes

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