DBMS > Apache Druid vs. Badger vs. Firebolt vs. IBM Cloudant

System Properties Comparison Apache Druid vs. Badger vs. Firebolt vs. IBM Cloudant

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Database as a Service offering based on Apache CouchDB

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Document store

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

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

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Website

druid.apache.org

github.com/dgraph-io/badger

www.firebolt.io

www.ibm.com/products/cloudant

Technical documentation

druid.apache.org/docs/latest/design

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

docs.firebolt.io

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation and contributors

DGraph Labs

Firebolt Analytics Inc.

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2012

2017

2020

2010

Current release

29.0.1, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

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

Erlang

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

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 for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

.Net
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
JavaScript (Node.js)
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

depending on storage layer

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users can be defined per database

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