DBMS > Apache Druid vs. Bangdb vs. Quasardb vs. RavenDB vs. SiteWhere

System Properties Comparison Apache Druid vs. Bangdb vs. Quasardb vs. RavenDB vs. SiteWhere

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

Converged and high performance database for device data, events, time series, document and graph

Distributed, high-performance timeseries database

Open Source Operational and Transactional Enterprise NoSQL Document Database

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

github.com/sitewhere/sitewhere

Technical documentation

druid.apache.org/docs/latest/design

docs.bangdb.com

doc.quasar.ai/master

ravendb.net/docs

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation and contributors

Sachin Sinha, BangDB

quasardb

Hibernating Rhinos

SiteWhere

Initial release

2012

2009

2010

Current release

29.0.1, April 2024

BangDB 2.0, October 2021

3.14.1, January 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD 3

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL version 3, commercial license available

Open Source

Common Public Attribution License Version 1.0

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

C, C++

C++

Java

Server operating systems

Linux
OS X
Unix

Linux

BSD
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

integer and binary

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

secondary, composite, nested, reverse, geospatial

yes

with tags

yes

SQL

Support of SQL

SQL for querying

SQL like support with command line tool

SQL-like query language

SQL-like query language (RQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol
RESTful HTTP API

HTTP API

.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 REST

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

consistent hashing

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication with selectable replication factor

Multi-source replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

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.

Immediate Consistency

Foreign keys

Referential integrity

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

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

Transient mode

User concepts

Access control

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

yes (enterprise version only)

Cryptographically strong user authentication and audit trail

Authorization levels configured per client per database

Users with fine-grained authorization concept

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