DBMS > Apache Druid vs. Fauna vs. Microsoft SQL Server vs. OpenQM

System Properties Comparison Apache Druid vs. Fauna vs. Microsoft SQL Server vs. OpenQM

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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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Multivalue DBMS

Secondary database models

Document store
Graph DBMS
Spatial 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	1.55
Rank	#143	Overall
	#26	Document stores
	#13	Graph DBMS
	#66	Relational DBMS
	#13	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Website

druid.apache.org

fauna.com

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

druid.apache.org/docs/latest/design

docs.fauna.com

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

Developer

Apache Software Foundation and contributors

Fauna, Inc.

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2012

2014

1989

1993

Current release

30.0.0, June 2024

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

Scala

C++

Server operating systems

Linux
OS X
Unix

hosted

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

consistent hashing

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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