DBMS > Apache Druid vs. Microsoft SQL Server vs. ObjectBox vs. Yanza

System Properties Comparison Apache Druid vs. Microsoft SQL Server vs. ObjectBox vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Microsofts flagship relational DBMS

Extremely fast embedded database for small devices, IoT and Mobile

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Object oriented DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Time Series DBMS

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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Website

druid.apache.org

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

objectbox.io

yanza.com

Technical documentation

druid.apache.org/docs/latest/design

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

docs.objectbox.io

Developer

Apache Software Foundation and contributors

Microsoft

ObjectBox Limited

Yanza

Initial release

2012

1989

2017

2015

Current release

29.0.1, April 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

Open Source

Apache License 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Android
iOS
Linux
macOS
Windows

Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

Proprietary native API

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

any language that supports HTTP calls

Server-side scripts

Stored procedures

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

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, but depending on the SQL-Server Edition

online/offline synchronization between client and server

none

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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