DBMS > AgensGraph vs. Apache Druid vs. Microsoft SQL Server vs. SAP Adaptive Server

System Properties Comparison AgensGraph vs. Apache Druid vs. Microsoft SQL Server vs. SAP Adaptive Server

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Microsofts flagship relational DBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	36.31
Rank	#25	Overall
	#17	Relational DBMS

Website

bitnine.net/agensgraph

druid.apache.org

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

www.sap.com/products/technology-platform/sybase-ase.html

Technical documentation

bitnine.net/documentation

druid.apache.org/docs/latest/design

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

help.sap.com/docs/SAP_ASE

Developer

Bitnine Global Inc.

Apache Software Foundation and contributors

Microsoft

SAP, Sybase

Initial release

2016

2012

1989

1987

Current release

2.1, December 2018

29.0.1, April 2024

SQL Server 2022, November 2022

16.0

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache license v2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

C and C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Data scheme

depending on used data model

yes

schema-less columns are supported

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

yes

SQL for querying

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
RESTful HTTP/JSON API

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

Supported programming languages

C
Java
JavaScript
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C
C++
Cobol
Java
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

yes

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

Java and Transact-SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

manual/auto, time-based

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, via HDFS, S3 or other storage engines

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

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

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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