DBMS > ArcadeDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SpaceTime vs. Splice Machine

System Properties Comparison ArcadeDB vs. Microsoft SQL Server vs. SAP SQL Anywhere vs. SpaceTime vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.02
Rank	#374	Overall
	#52	Document stores
	#38	Graph DBMS
	#56	Key-value stores
	#38	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

arcadedb.com

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

www.sap.com/products/technology-platform/sql-anywhere.html

www.mireo.com/spacetime

splicemachine.com

Technical documentation

docs.arcadedb.com

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

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

Developer

Arcade Data

Microsoft

SAP

formerly Sybase

Mireo

Splice Machine

Initial release

2021

1989

1992

2020

2014

Current release

September 2021

SQL Server 2022, November 2022

17, July 2015

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

Open Source

AGPL 3.0, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

All OS with a Java VM

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

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

SQL-like query language, no joins

yes

A subset of ANSI SQL is implemented

yes

APIs and other access methods

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)

ADO.NET
HTTP API
JDBC
ODBC

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
C++
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

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

yes, in C/C++, Java, .Net or Perl

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Fixed-grid hypercubes

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

Real-time block device replication (DRBD)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

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

yes

Access rights for users, groups and roles according to SQL-standard

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