DBMS > Apache Druid vs. Infobright vs. RavenDB vs. Riak KV

System Properties Comparison Apache Druid vs. Infobright vs. RavenDB vs. Riak KV

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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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Open Source Operational and Transactional Enterprise NoSQL Document Database

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

druid.apache.org

ignitetech.com/softwarelibrary/infobrightdb

ravendb.net

Technical documentation

druid.apache.org/docs/latest/design

ravendb.net/docs

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Apache Software Foundation and contributors

Ignite Technologies Inc.; formerly InfoBright Inc.

Hibernating Rhinos

OpenSource, formerly Basho Technologies

Initial release

2012

2005

2010

2009

Current release

30.0.0, June 2024

5.4, July 2022

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

AGPL version 3, commercial license available

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X

Data scheme

yes

schema-less columns are supported

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

Knowledge Grid Technology used instead

yes

restricted

SQL

Support of SQL

SQL for querying

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Multi-source replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Eventual Consistency

Foreign keys

Referential integrity

links between data sets can be stored

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Authorization levels configured per client per database

yes, using Riak Security

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More resources

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