DBMS > Altibase vs. Apache Druid vs. ArcadeDB vs. Microsoft SQL Server

System Properties Comparison Altibase vs. Apache Druid vs. ArcadeDB vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

altibase.com

druid.apache.org

arcadedb.com

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

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

druid.apache.org/docs/latest/design

docs.arcadedb.com

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

Developer

Altibase

Apache Software Foundation and contributors

Arcade Data

Microsoft

Initial release

1999

2012

2021

1989

Current release

v7.3, 2023, August 2023

29.0.1, April 2024

September 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C++

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Unix

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

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

ANSI SQL-92

SQL for querying

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
RESTful HTTP/JSON API

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

Supported programming languages

C
C++
Java

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

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

Server-side scripts

Stored procedures

stored procedures and stored functions

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

Triggers

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Source-replica replication

yes, but depending on the SQL-Server Edition

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

relationship in graphs

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

fine grained access rights according to SQL-standard

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

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