DBMS > SAP Advantage Database Server vs. SiteWhere vs. SpatiaLite vs. Splice Machine

System Properties Comparison SAP Advantage Database Server vs. SiteWhere vs. SpatiaLite vs. Splice Machine

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Low-cost RDBMS with access to ISAM and FoxPro data structures

M2M integration platform for persisting/querying time series data

Spatial extension of SQLite

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

Primary database model

Secondary database models

Relational DBMS

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

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.sap.com/products/advantage-database-server.html

github.com/sitewhere/sitewhere

www.gaia-gis.it/fossil/libspatialite/index

splicemachine.com

Technical documentation

sitewhere1.sitewhere.io/index.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

splicemachine.com/how-it-works

Developer

Sybase, SAP

SiteWhere

Alessandro Furieri

Splice Machine

Initial release

1993

2010

2008

2014

Current release

5.0.0, August 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

server-less

Linux
OS X
Solaris
Windows

Data scheme

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

HTTP REST

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Delphi
Perl
PHP

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

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

selectable replication factor

based on HBase

none

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

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.

caching of (temporary) tables can be configured

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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

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More resources

DB-Engines blog posts

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6 April 2021, Matthias Gelbmann

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