DBMS > SAP Advantage Database Server vs. Spark SQL vs. TDSQL for MySQL vs. ToroDB

System Properties Comparison SAP Advantage Database Server vs. Spark SQL vs. TDSQL for MySQL vs. ToroDB

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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.

ToroDB 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

Spark SQL is a component on top of 'Spark Core' for structured data processing

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

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

spark.apache.org/sql

www.tencentcloud.com/products/dcdb

github.com/torodb/server

Technical documentation

spark.apache.org/docs/latest/sql-programming-guide.html

www.tencentcloud.com/document/product/1042

Developer

Sybase, SAP

Apache Software Foundation

Tencent

8Kdata

Initial release

1993

2014

2013

2016

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Scala

Java

Server operating systems

Linux
Windows

Linux
OS X
Windows

hosted

All OS with a Java 7 VM

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

SQL-like DML and DDL statements

yes

APIs and other access methods

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

Delphi
Perl
PHP

Java
Python
R
Scala

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes, utilizing Spark Core

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

none

Multi-source replication
Source-replica 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

Eventual Consistency
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.

caching of (temporary) tables can be configured

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Access rights for users and roles

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