DBMS > Apache Druid vs. BaseX vs. Microsoft SQL Server vs. OrientDB vs. Quasardb

System Properties Comparison Apache Druid vs. BaseX vs. Microsoft SQL Server vs. OrientDB vs. Quasardb

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

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

Distributed, high-performance timeseries database

Primary database model

Relational DBMS
Time Series DBMS

Native XML DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial 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	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

druid.apache.org

basex.org

www.microsoft.com/en-us/sql-server

orientdb.org

quasar.ai

Technical documentation

druid.apache.org/docs/latest/design

docs.basex.org

learn.microsoft.com/en-US/sql/sql-server

www.orientdb.com/docs/last/index.html

doc.quasar.ai/master

Developer

Apache Software Foundation and contributors

BaseX GmbH

Microsoft

OrientDB LTD; CallidusCloud; SAP

quasardb

Initial release

2012

2007

1989

2010

2009

Current release

29.0.1, April 2024

10.7, August 2023

SQL Server 2022, November 2022

3.2.29, March 2024

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD license

commercial

restricted free version is available

Open Source

Apache version 2

commercial

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

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Linux
Windows

All OS with a Java JDK (>= JDK 6)

BSD
Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

integer and binary

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.

yes

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL for querying

yes

SQL-like query language, no joins

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java, Javascript

Triggers

yes

via events

yes

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes, but depending on the SQL-Server Edition

Multi-source replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

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

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Cryptographically strong user authentication and audit trail

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